System and method for output compensation in flow sensors

ABSTRACT

A system for monitoring and controlling flow rate of a fluid through a valve, the system including a flow rate sensor configured to measure the flow rate of the fluid through the valve, and a controller in communication with the flow rate sensor. The controller is configured to receive the measured flow rate from the flow rate sensor and determine if the measured flow rate is equal to a predetermined flow rate value. In response to determining equality, the controller is configured to determine a minimum valve position threshold (x min ), and determine a minimum flow rate threshold (y min ) corresponding to x min . The controller is further configured to calculate a corrected flow rate (ŷ f ) using x min , y min , and an indication of valve position (v). Additionally, the controller is configured to control a valve operation using the corrected flow rate (ŷ f ).

BACKGROUND

The present disclosure relates generally to building management systemsand associated devices. More particularly, the present disclosurerelates to a controller and actuator with valve control capabilitieswithin an HVAC system.

HVAC actuators are used to operate a wide variety of HVAC componentssuch as air dampers, fluid valves, air handling units, and othercomponents that are typically used in HVAC systems. For example, anactuator may be coupled to a valve, or other movable equipment in anHVAC and may be used to drive the equipment (e.g., the valve) between anopen position and a closed position. A conventional actuator includes amotor and a drive device (e.g., a hub, a drive train, etc.) that isdriven by the motor and coupled to the HVAC component.

The HVAC industry is moving towards the use of control valves capable ofmaintaining desired water flows regardless of time-varying pressureconditions in the pipes. Some valves are part of a control loop thatincludes a flow rate sensor that measures the flow rate and sends asignal to a feedback controller. The feedback controller then sends asignal to an actuator to adjust the opening of the valve to achieve thedesired flow rate.

The flow rate sensors in the flow control loops have a working rangebetween a minimum and maximum readable flow at which they are configuredto provide reliable flow rate measurements. Therefore, flow ratesoutside of the working range may be unreliable. Accordingly, it would beadvantageous to compensate for when the actual flow rate values arebelow the minimum readable flow corresponding to the flow rate sensor.

SUMMARY

One implementation of the present disclosure is a system for monitoringand controlling flow rate of a fluid through a valve, the systemincluding a flow rate sensor configured to measure the flow rate of thefluid through the valve, and a controller in communication with the flowrate sensor. The controller is configured to receive the measured flowrate from the flow rate sensor and determine if the measured flow rateis equal to a predetermined flow rate value. In response to determiningequality, the controller is configured to determine a minimum valveposition threshold (x_(min)), and determine a minimum flow ratethreshold (y_(min)) corresponding to x_(min). The controller is furtherconfigured to calculate a corrected flow rate (ŷ_(f)) using x_(min),y_(min), and an indication of valve position (v). Additionally, thecontroller is configured to control a valve operation using thecorrected flow rate (ŷ_(f)).

In some embodiments, the system further includes a differential pressuresensor, wherein the indication of valve position (v) is a change inpressure across the valve (Δp) provided by the differential pressuresensor. In some embodiments, the controller includes a valve identifierconfigured to identify a valve type of the valve and use the valve typeto determine at least one corresponding valve equation, the controllerconfigured to calculate the corrected flow rate using the at least onecorresponding valve equation and the change in pressure across the valve(Δp).

In some embodiments, the controller is configured to calculate thecorrected flow rate ŷ_(f), by performing an interpolation between thepredetermined flow rate value and the minimum flow rate thresholdy_(min) as a function of the indication of valve position (v), theinterpolation including a polynomial function

${\hat{y}}_{f} = {\frac{y_{\min}}{x_{\min}^{n}}v^{n}}$where n is a degree of the polynomial function.

In some embodiments, the controller includes a position detectorconfigured to determine a position of the valve (x_(i)), whereinindication of valve position (v) is the position of the valve x_(i).

In some embodiments, the controller is configured to calculate thecorrected flow rate ŷ_(f), by performing a an exponential interpolationbetween the predetermined flow rate value and the minimum flow ratethreshold y_(min) as a function of the indication of valve position (v),the exponential interpolation including an exponential functionŷ_(f)=y_(min)b^(−x) ^(min) b^(v) where b is a constant.

In some embodiments, the indication of valve position (v) is a positionof the valve (x_(i)), and in response to a determination that themeasured flow rate is not equal to the predetermined flow rate value,the controller is configured to determine a minimum valve positionthreshold ({circumflex over (x)}_(min)), set {circumflex over (x)}_(min)equal to a minimum value of {circumflex over (x)}_(min) and x_(i), andset x_(min) equal to {circumflex over (x)}_(min). Additionally, inresponse to a determination that the measured flow rate is equal to thepredetermined flow rate value, the controller is configured to determinea minimum valve position threshold ({circumflex over (x)}_(min)), set{circumflex over (x)}_(min) equal to a maximum value of {circumflex over(x)}_(min) and x_(i), and set x_(min) equal to {circumflex over(x)}_(min).

In some embodiments, the controller is configured to determine y_(min)by determining a maximum rating (y_(max)) of the flow rate sensor,calculating an estimated minimum flow rate value (ŷ_(min)), and settingy_(min) equal to ŷ_(min).

One implementation of the present disclosure is a system for monitoringand controlling flow rate of a fluid through a valve, the systemincluding a valve configured to regulate a flow of a fluid through aconduit, an actuator coupled to the valve and configured to drive thevalve between multiple positions, and a flow rate sensor configured tomeasure the flow rate of the fluid through the valve. Further, thesystem includes a controller in communication with the actuator and theflow rate sensor and configured to receive the measured flow rate, anddetermine if the measured flow rate is equal to zero. The controller isfurther configured to, in response to a determination that the measuredflow rate is equal to zero, determine a minimum valve position threshold(x_(min)), and determine a minimum flow rate threshold (y_(min)) usingx_(min). Additionally, the controller is configured to calculate acorrected flow rate (ŷ_(f)) by performing an interpolation between zeroand y_(min) and using a valve opening position (x_(i)) as an input to aninterpolation function, and control a valve operation using thecorrected flow rate. The controller is further configured to, inresponse to a determination that the measured flow rate is greater thanzero, control a valve operation using the measured flow rate.

In some embodiments, the controller is configured to determine x_(min)by determining an estimated minimum flow rate threshold ({circumflexover (x)}_(min)), and setting x_(min) equal to {circumflex over(x)}_(min).

In some embodiments, the controller is configured to initialize{circumflex over (x)}_(min) to 100.

In some embodiments, the controller is configured to update {circumflexover (x)}_(min,left) by determining the valve opening position (x_(i)),and setting {circumflex over (x)}_(min,left) to a maximum value of{circumflex over (x)}_(min,left) and x_(i).

In some embodiments, in response to a determination that the measuredflow rate is equal to zero, the controller is configured to update{circumflex over (x)}_(min) by determining the valve opening position(x_(i)), and setting {circumflex over (x)}_(min) to a maximum value of{circumflex over (x)}_(min) and x_(i).

In some embodiments, the controller is configured to determine y_(min)by determining a maximum rating (y_(max)) of the flow rate sensor,calculating an estimated minimum flow rate value (ŷ_(min)), and settingy_(min) equal to ŷ_(min).

In some embodiments, the controller is configured to initialize ŷ_(min)to y_(max) and configured to update ŷ_(min) each time the measured flowrate (y_(f)) is greater than zero.

In some embodiments, the controller is configured to update ŷ_(min) bydetermining the measured flow rate (y_(f)), and setting ŷ_(min) to aminimum value of ŷ_(min) and y_(f).

One implementation of the present disclosure is a method for monitoringand controlling flow rate of a fluid through a valve, the methodincluding measuring a flow rate, and determining if the flow rate isequal to zero. In response to a determination that the flow rate isequal to zero, the method further includes determining a minimum valveposition threshold (x_(min)), determining a minimum flow rate threshold(y_(min)) corresponding to x_(min), calculating a corrected flow rate(ŷ_(f)) using x_(min), y_(min), and a valve opening position (x_(i)),and controlling a valve operation using the corrected flow rate (ŷ_(f)).In some embodiments, the method includes, in response to a determinationthat the flow rate is not equal to zero, determining an estimatedminimum valve position threshold ({circumflex over (x)}_(min)), andsetting {circumflex over (x)}_(min) equal to a minimum value of{circumflex over (x)}_(min) and x_(i). The method further includes inresponse to a determination that the flow rate is equal to zero,determining the estimated minimum valve position threshold ({circumflexover (x)}_(min)), and setting {circumflex over (x)}_(min) equal to amaximum value of {circumflex over (x)}_(min) and x_(i). The methodfurther includes initializing a filtered estimate (x _(min)) to{circumflex over (x)}_(min), and filtering {circumflex over (x)}_(min)using a filtering equation comprising x _(min)=x _(min)+e^(−h/τ) ^(a) (x_(min)−x _(min)) where h is a sample rate and τ_(a) is a time constant.Additionally, the method includes setting {circumflex over (x)}_(min)equal to x _(min).

In some embodiments, determining y _(min) includes determining a maximumrating (y_(max)) of the flow rate sensor, calculating an estimatedminimum flow rate value (ŷ_(min)), and setting y_(min) equal to ŷ_(min).

In some embodiments, calculating the corrected flow rate ŷ_(f) includesperforming an interpolation between zero and the minimum flow ratethreshold y_(min) as a function of the valve opening position (x_(i)),the interpolation including a polynomial function

${\hat{y}}_{f} = {\frac{y_{\min}}{x_{\min}^{n}}x_{i}^{n}}$where n is a degree of the polynomial function.

Those skilled in the art will appreciate that the summary isillustrative only and is not intended to be in any way limiting. Otheraspects, inventive features, and advantages of the devices and/orprocesses described herein, as defined solely by the claims, will becomeapparent in the detailed description set forth herein and taken inconjunction with the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a drawing of a building equipped with a HVAC system, accordingto some embodiments.

FIG. 2 is a block diagram of a waterside system that may be used inconjunction with the building of FIG. 1, according to some embodiments.

FIG. 3 is a block diagram of an airside system that may be used inconjunction with the building of FIG. 1, according to some embodiments.

FIG. 4 is a block diagram of a building management system (BMS) whichmay be used to monitor and control the building of FIG. 1, according tosome embodiments.

FIG. 5 is a graph illustrating a conventional working rangecorresponding to a flow rate sensor that may be used in conjunction withthe building of FIG. 1, according to some embodiments.

FIG. 6 is a block diagram of an actuator, valve device, and controllerthat may be implemented in the HVAC system of FIG. 1, according to someembodiments.

FIG. 7 is a block diagram of an integrated smart actuator and valvedevice that may be implemented in the HVAC system of FIG. 1, accordingto some embodiments.

FIG. 8 is a graph illustrating an example profile of the flow ratemeasured by a flow rate sensor for a given opening of a valve, accordingto some embodiments.

FIG. 9 is a block diagram of a control system with position and flowrate inputs to a controller that may be implemented in the HVAC systemof FIG. 1, according to some embodiments.

FIG. 10 is a block diagram of another control system with a pressuredifferential values and flow rate inputs to a controller that may beimplemented in the HVAC system of FIG. 1, according to some embodiments.

FIG. 11 is a flowchart of a flow rate correction method which may beperformed by the controller of FIG. 9, according to some embodiments.

FIG. 12 is a flowchart of a flow rate correction method which may beperformed by the controller of FIG. 10, according to some embodiments.

FIG. 13 is a flowchart of a process for estimating a minimum valveposition threshold, according to some embodiments.

FIG. 14 is a flowchart of a process for determining a first minimumvalve position threshold, according to some embodiments.

FIG. 15 is a flowchart of a process for determining a second minimumvalve position threshold, according to some embodiments.

FIG. 16 is a flowchart of a process for estimating a minimum flow ratethreshold, according to some embodiments.

FIG. 17 is a flowchart of a process for estimating a minimum valveposition threshold, according to some embodiments.

FIG. 18 is a flowchart of a process for filtering an estimated minimumvalve position threshold, according to some embodiments.

FIG. 19 is a flowchart of another flow rate correction method which maybe performed by the controller of FIG. 9, according to some embodiments.

FIG. 20A is a table of flow rate sensor parameters used in an examplesimulation, according to some embodiments.

FIG. 20B is a block diagram of the example simulation of FIG. 20A,according to some embodiments.

FIG. 20C is a block diagram of a simulation corresponding to a benchmarksystem, according to some embodiments.

FIG. 20D is a graph illustrating the simulation results from the blockdiagrams of FIG. 20B and FIG. 20C.

FIG. 21 is a graph illustrating the function of a proportional variabledeadband controller (PVDC) which may be implemented in the presentdisclosure, according to some embodiments.

DETAILED DESCRIPTION

Overview

Referring generally to the FIGURES, systems and methods for estimatingflow rate values are shown, according to various exemplary embodiments.As described above, typical flow rate sensors within flow control loopshave a working range extending between a minimum readable flow rate (asused herein, a minimum flow rate threshold) and a maximum readable flowrate (as used herein, a maximum rating of a flow sensor). Within theworking range, the flow rate sensors are able to provide reliablemeasurements. However, flow rates measured outside of the working rangeare considered unreliable. For example, flow rate values below theminimum flow rate threshold (y_(min)) read as zero. Conversely, flowrate values above the maximum rating of the flow sensor (y_(max)) mayread as saturations at the maximum flow. In some situations, thebehavior of the flow rate sensors outside of the working range mayaffect the ability of a flow controller to reach desired flow setpoints.

In practice, the instrumentation of a plant is typically overdesigned.Accordingly, it is very likely that a flow rate sensor be installed witha maximum rating larger than the actual maximum flow rate in the valve.This also means that the flow rate sensor may have a minimum flow ratethreshold larger than the actual operational flow rates found in thevalve. A large minimum flow rate threshold in the flow rate sensor maymake the system uncontrollable if a large portion of the required flowrate is below that value. Accordingly, the present disclosure includessystems and methods for estimating flow rate values outside of theworking range corresponding to the flow rate sensor.

The present disclosure includes an algorithm that uses the output fromthe flow controller or the position of an actuator, to interpolatebetween the estimated minimum flow rate threshold and estimated minimumvalve position threshold, and a zero flow rate and zero valve openingposition, to estimate a flow rate value.

In some embodiments, the flow rate sensor output may correspond to afunction that produces a standard flow rate measurement if themeasurement is non-zero, or a corrected flow rate if the measurement iszero.

In some embodiments, a linear approximation of the measured flow rate isused. In some situations, it may be desired to extend a line(graphically) between the origin and the point (x_(min), y_(min)), wherex_(min) corresponds to a minimum valve position threshold and y_(min)corresponds to a minimum flow rate threshold. In other situations, itmay be beneficial to use a different method of approximation (e.g.,quadratic, exponential, cubic, n^(th) order polynomial, etc). Severalmethods of approximation are described herein.

In some embodiments, a corrected flow rate may be calculated using anindication of valve position. In some situations, it may be beneficialto use a change in pressure through the valve as the indication of valveposition. The change in pressure may be measured via a differentialpressure sensor. In other situations, it may be beneficial to use avalve opening position as the indication of valve position.

In some embodiments, the valve type may be used to determine valveequations. The valve equations may be implemented to determine acorrected flow rate.

In some embodiments, x_(min), may be known. In other embodiments,x_(min), may be estimated using various calculations, as discussed indetail below. Similarly, y_(min) may be known or estimated using variouscalculations, as discussed in detail below. In some situations, it maybe beneficial to initialize and/or estimate y_(min) to be y_(max).Alternatively, y_(min) may be initialized and/or estimated to adifferent value, such as a percentage of y_(max). As one non-limitingexample, y_(min) may be initialized and/or estimated to be 0.2y_(max).

Advantageously, the systems and methods described herein may enable aflow controller to reach desired flow setpoints, even when the flow ratesensors are measuring outside of the working range. The overallperformance of the control system may be improved, as the presentdisclosure overcomes the issue of having flow rate readings of zero whenthere is clearly a flow going through the valve. Additional advantagesof the present disclosure will become apparent as the variousembodiments are described.

Building HVAC Systems and Building Management Systems

Referring now to FIGS. 1-4, several building management systems (BMS)and HVAC systems in which the systems and methods of the presentdisclosure may be implemented are shown, according to some embodiments.In brief overview, FIG. 1 shows a building 10 equipped with a HVACsystem 100. FIG. 2 is a block diagram of a waterside system 200 whichmay be used to serve building 10. FIG. 3 is a block diagram of anairside system 300 which may be used to serve building 10. FIG. 4 is ablock diagram of a BMS which may be used to monitor and control building10.

Building and HVAC System

Referring particularly to FIG. 1, a perspective view of a building 10 isshown. Building 10 is served by a BMS. A BMS is, in general, a system ofdevices configured to control, monitor, and manage equipment in oraround a building or building area. A BMS may include, for example, aHVAC system, a security system, a lighting system, a fire alertingsystem, any other system that is capable of managing building functionsor devices, or any combination thereof.

The BMS that serves building 10 includes a HVAC system 100. HVAC system100 may include a plurality of HVAC devices (e.g., heaters, chillers,air handling units, pumps, fans, thermal energy storage, etc.)configured to provide heating, cooling, ventilation, or other servicesfor building 10. For example, HVAC system 100 is shown to include awaterside system 120 and an airside system 130. Waterside system 120 mayprovide a heated or chilled fluid to an air handling unit of airsidesystem 130. Airside system 130 may use the heated or chilled fluid toheat or cool an airflow provided to building 10. An exemplary watersidesystem and airside system which may be used in HVAC system 100 aredescribed in greater detail with reference to FIGS. 2-3.

HVAC system 100 is shown to include a chiller 102, a boiler 104, and arooftop air handling unit (AHU) 106. Waterside system 120 may use boiler104 and chiller 102 to heat or cool a working fluid (e.g., water,glycol, etc.) and may circulate the working fluid to AHU 106. In variousembodiments, the HVAC devices of waterside system 120 may be located inor around building 10 (as shown in FIG. 1) or at an offsite locationsuch as a central plant (e.g., a chiller plant, a steam plant, a heatplant, etc.). The working fluid may be heated in boiler 104 or cooled inchiller 102, depending on whether heating or cooling is required inbuilding 10. Boiler 104 may add heat to the circulated fluid, forexample, by burning a combustible material (e.g., natural gas) or usingan electric heating element. Chiller 102 may place the circulated fluidin a heat exchange relationship with another fluid (e.g., a refrigerant)in a heat exchanger (e.g., an evaporator) to absorb heat from thecirculated fluid. The working fluid from chiller 102 and/or boiler 104may be transported to AHU 106 via piping 108.

AHU 106 may place the working fluid in a heat exchange relationship withan airflow passing through AHU 106 (e.g., via one or more stages ofcooling coils and/or heating coils). The airflow may be, for example,outside air, return air from within building 10, or a combination ofboth. AHU 106 may transfer heat between the airflow and the workingfluid to provide heating or cooling for the airflow. For example, AHU106 may include one or more fans or blowers configured to pass theairflow over or through a heat exchanger containing the working fluid.The working fluid may then return to chiller 102 or boiler 104 viapiping 110.

Airside system 130 may deliver the airflow supplied by AHU 106 (i.e.,the supply airflow) to building 10 via air supply ducts 112 and mayprovide return air from building 10 to AHU 106 via air return ducts 114.In some embodiments, airside system 130 includes multiple variable airvolume (VAV) units 116. For example, airside system 130 is shown toinclude a separate VAV unit 116 on each floor or zone of building 10.VAV units 116 may include dampers or other flow control elements thatmay be operated to control an amount of the supply airflow provided toindividual zones of building 10. In other embodiments, airside system130 delivers the supply airflow into one or more zones of building 10(e.g., via supply ducts 112) without using intermediate VAV units 116 orother flow control elements. AHU 106 may include various sensors (e.g.,temperature sensors, pressure sensors, etc.) configured to measureattributes of the supply airflow. AHU 106 may receive input from sensorslocated within AHU 106 and/or within the building zone and may adjustthe flow rate, temperature, or other attributes of the supply airflowthrough AHU 106 to achieve setpoint conditions for the building zone.

Waterside System

Referring now to FIG. 2, a block diagram of a waterside system 200 isshown, according to some embodiments. In various embodiments, watersidesystem 200 may supplement or replace waterside system 120 in HVAC system100 or may be implemented separate from HVAC system 100. Whenimplemented in HVAC system 100, waterside system 200 may include asubset of the HVAC devices in HVAC system 100 (e.g., boiler 104, chiller102, pumps, valves, etc.) and may operate to supply a heated or chilledfluid to AHU 106. The HVAC devices of waterside system 200 may belocated within building 10 (e.g., as components of waterside system 120)or at an offsite location such as a central plant.

In FIG. 2, waterside system 200 is shown as a central plant having aplurality of subplants 202-212. Subplants 202-212 are shown to include aheater subplant 202, a heat recovery chiller subplant 204, a chillersubplant 206, a cooling tower subplant 208, a hot thermal energy storage(TES) subplant 210, and a cold thermal energy storage (TES) subplant212. Subplants 202-212 consume resources (e.g., water, natural gas,electricity, etc.) from utilities to serve thermal energy loads (e.g.,hot water, cold water, heating, cooling, etc.) of a building or campus.For example, heater subplant 202 may be configured to heat water in ahot water loop 214 that circulates the hot water between heater subplant202 and building 10. Chiller subplant 206 may be configured to chillwater in a cold water loop 216 that circulates the cold water betweenchiller subplant 206 building 10. Heat recovery chiller subplant 204 maybe configured to transfer heat from cold water loop 216 to hot waterloop 214 to provide additional heating for the hot water and additionalcooling for the cold water. Condenser water loop 218 may absorb heatfrom the cold water in chiller subplant 206 and reject the absorbed heatin cooling tower subplant 208 or transfer the absorbed heat to hot waterloop 214. Hot TES subplant 210 and cold TES subplant 212 may store hotand cold thermal energy, respectively, for subsequent use.

Hot water loop 214 and cold water loop 216 may deliver the heated and/orchilled water to air handlers located on the rooftop of building 10(e.g., AHU 106) or to individual floors or zones of building 10 (e.g.,VAV units 116). The air handlers push air past heat exchangers (e.g.,heating coils or cooling coils) through which the water flows to provideheating or cooling for the air. The heated or cooled air may bedelivered to individual zones of building 10 to serve thermal energyloads of building 10. The water then returns to subplants 202-212 toreceive further heating or cooling.

Although subplants 202-212 are shown and described as heating andcooling water for circulation to a building, it is understood that anyother type of working fluid (e.g., glycol, CO2, etc.) may be used inplace of or in addition to water to serve thermal energy loads. In otherembodiments, subplants 202-212 may provide heating and/or coolingdirectly to the building or campus without requiring an intermediateheat transfer fluid. These and other variations to waterside system 200are within the teachings of the present disclosure.

Each of subplants 202-212 may include a variety of equipment configuredto facilitate the functions of the subplant. For example, heatersubplant 202 is shown to include a plurality of heating elements 220(e.g., boilers, electric heaters, etc.) configured to add heat to thehot water in hot water loop 214. Heater subplant 202 is also shown toinclude several pumps 222 and 224 configured to circulate the hot waterin hot water loop 214 and to control the flow rate of the hot waterthrough individual heating elements 220. Chiller subplant 206 is shownto include a plurality of chillers 232 configured to remove heat fromthe cold water in cold water loop 216. Chiller subplant 206 is alsoshown to include several pumps 234 and 236 configured to circulate thecold water in cold water loop 216 and to control the flow rate of thecold water through individual chillers 232.

Heat recovery chiller subplant 204 is shown to include a plurality ofheat recovery heat exchangers 226 (e.g., refrigeration circuits)configured to transfer heat from cold water loop 216 to hot water loop214. Heat recovery chiller subplant 204 is also shown to include severalpumps 228 and 230 configured to circulate the hot water and/or coldwater through heat recovery heat exchangers 226 and to control the flowrate of the water through individual heat recovery heat exchangers 226.Cooling tower subplant 208 is shown to include a plurality of coolingtowers 238 configured to remove heat from the condenser water incondenser water loop 218. Cooling tower subplant 208 is also shown toinclude several pumps 240 configured to circulate the condenser water incondenser water loop 218 and to control the flow rate of the condenserwater through individual cooling towers 238.

Hot TES subplant 210 is shown to include a hot TES tank 242 configuredto store the hot water for later use. Hot TES subplant 210 may alsoinclude one or more pumps or valves configured to control the flow rateof the hot water into or out of hot TES tank 242. Cold TES subplant 212is shown to include cold TES tanks 244 configured to store the coldwater for later use. Cold TES subplant 212 may also include one or morepumps or valves configured to control the flow rate of the cold waterinto or out of cold TES tanks 244.

In some embodiments, one or more of the pumps in waterside system 200(e.g., pumps 222, 224, 228, 230, 234, 236, and/or 240) or pipelines inwaterside system 200 include an isolation valve associated therewith.Isolation valves may be integrated with the pumps or positioned upstreamor downstream of the pumps to control the fluid flows in watersidesystem 200. In various embodiments, waterside system 200 may includemore, fewer, or different types of devices and/or subplants based on theparticular configuration of waterside system 200 and the types of loadsserved by waterside system 200.

Airside System

Referring now to FIG. 3, a block diagram of an airside system 300 isshown, according to some embodiments. In various embodiments, airsidesystem 300 may supplement or replace airside system 130 in HVAC system100 or may be implemented separate from HVAC system 100. Whenimplemented in HVAC system 100, airside system 300 may include a subsetof the HVAC devices in HVAC system 100 (e.g., AHU 106, VAV units 116,ducts 112-114, fans, dampers, etc.) and may be located in or aroundbuilding 10. Airside system 300 may operate to heat or cool an airflowprovided to building 10 using a heated or chilled fluid provided bywaterside system 200.

In FIG. 3, airside system 300 is shown to include an economizer-type airhandling unit (AHU) 302. Economizer-type AHUs vary the amount of outsideair and return air used by the air handling unit for heating or cooling.For example, AHU 302 may receive return air 304 from building zone 306via return air duct 308 and may deliver supply air 310 to building zone306 via supply air duct 312. In some embodiments, AHU 302 is a rooftopunit located on the roof of building 10 (e.g., AHU 106 as shown inFIG. 1) or otherwise positioned to receive both return air 304 andoutside air 314. AHU 302 may be configured to operate exhaust air damper316, mixing damper 318, and outside air damper 320 to control an amountof outside air 314 and return air 304 that combine to form supply air310. Any return air 304 that does not pass through mixing damper 318 maybe exhausted from AHU 302 through exhaust damper 316 as exhaust air 322.

Each of dampers 316-320 may be operated by an actuator. For example,exhaust air damper 316 may be operated by actuator 324, mixing damper318 may be operated by actuator 326, and outside air damper 320 may beoperated by actuator 328. Actuators 324-328 may communicate with an AHUcontroller 330 via a communications link 332. Actuators 324-328 mayreceive control signals from AHU controller 330 and may provide feedbacksignals to AHU controller 330. Feedback signals may include, forexample, an indication of a current actuator or damper position, anamount of torque or force exerted by the actuator, diagnosticinformation (e.g., results of diagnostic tests performed by actuators324-328), status information, commissioning information, configurationsettings, calibration data, and/or other types of information or datathat may be collected, stored, or used by actuators 324-328. AHUcontroller 330 may be an economizer controller configured to use one ormore control algorithms (e.g., state-based algorithms, extremum seekingcontrol (ESC) algorithms, proportional-integral (PI) control algorithms,proportional-integral-derivative (PID) control algorithms, modelpredictive control (MPC) algorithms, feedback control algorithms, etc.)to control actuators 324-328.

Still referring to FIG. 3, AHU 302 is shown to include a cooling coil334, a heating coil 336, and a fan 338 positioned within supply air duct312. Fan 338 may be configured to force supply air 310 through coolingcoil 334 and/or heating coil 336 and provide supply air 310 to buildingzone 306. AHU controller 330 may communicate with fan 338 viacommunications link 340 to control a flow rate of supply air 310. Insome embodiments, AHU controller 330 controls an amount of heating orcooling applied to supply air 310 by modulating a speed of fan 338.

Cooling coil 334 may receive a chilled fluid from waterside system 200(e.g., from cold water loop 216) via piping 342 and may return thechilled fluid to waterside system 200 via piping 344. Valve 346 may bepositioned along piping 342 or piping 344 to control a flow rate of thechilled fluid through cooling coil 334. In some embodiments, coolingcoil 334 includes multiple stages of cooling coils that may beindependently activated and deactivated (e.g., by AHU controller 330, byBMS controller 366, etc.) to modulate an amount of cooling applied tosupply air 310.

Heating coil 336 may receive a heated fluid from waterside system200(e.g., from hot water loop 214) via piping 348 and may return theheated fluid to waterside system 200 via piping 350. Valve 352 may bepositioned along piping 348 or piping 350 to control a flow rate of theheated fluid through heating coil 336. In some embodiments, heating coil336 includes multiple stages of heating coils that may be independentlyactivated and deactivated (e.g., by AHU controller 330, by BMScontroller 366, etc.) to modulate an amount of heating applied to supplyair 310.

Each of valves 346 and 352 may be controlled by an actuator. Forexample, valve 346 may be controlled by actuator 354 and valve 352 maybe controlled by actuator 356. Actuators 354-356 may communicate withAHU controller 330 via communications links 358-360. Actuators 354-356may receive control signals from AHU controller 330 and may providefeedback signals to controller 330. In some embodiments, AHU controller330 receives a measurement of the supply air temperature from atemperature sensor 362 positioned in supply air duct 312 (e.g.,downstream of cooling coil 334 and/or heating coil 336). AHU controller330 may also receive a measurement of the temperature of building zone306 from a temperature sensor 364 located in building zone 306.

In some embodiments, AHU controller 330 operates valves 346 and 352 viaactuators 354-356 to modulate an amount of heating or cooling providedto supply air 310 (e.g., to achieve a setpoint temperature for supplyair 310 or to maintain the temperature of supply air 310 within asetpoint temperature range). The positions of valves 346 and 352 affectthe amount of heating or cooling provided to supply air 310 by coolingcoil 334 or heating coil 336 and may correlate with the amount of energyconsumed to achieve a desired supply air temperature. AHU 330 maycontrol the temperature of supply air 310 and/or building zone 306 byactivating or deactivating coils 334-336, adjusting a speed of fan 338,or a combination of both.

Still referring to FIG. 3, airside system 300 is shown to include abuilding management system (BMS) controller 366 and a client device 368.BMS controller 366 may include one or more computer systems (e.g.,servers, supervisory controllers, subsystem controllers, etc.) thatserve as system level controllers, application or data servers, headnodes, or master controllers for airside system 300, waterside system200, HVAC system 100, and/or other controllable systems that servebuilding 10. BMS controller 366 may communicate with multiple downstreambuilding systems or subsystems (e.g., HVAC system 100, a securitysystem, a lighting system, waterside system 200, etc.) via acommunications link 370 according to like or disparate protocols (e.g.,LON, BACnet, etc.). In various embodiments, AHU controller 330 and BMScontroller 366 may be separate (as shown in FIG. 3) or integrated. In anintegrated implementation, AHU controller 330 may be a software moduleconfigured for execution by a processor of BMS controller 366.

In some embodiments, AHU controller 330 receives information from BMScontroller 366 (e.g., commands, setpoints, operating boundaries, etc.)and provides information to BMS controller 366 (e.g., temperaturemeasurements, valve or actuator positions, operating statuses,diagnostics, etc.). For example, AHU controller 330 may provide BMScontroller 366 with temperature measurements from temperature sensors362-364, equipment on/off states, equipment operating capacities, and/orany other information that may be used by BMS controller 366 to monitoror control a variable state or condition within building zone 306.

Client device 368 may include one or more human-machine interfaces orclient interfaces (e.g., graphical user interfaces, reportinginterfaces, text-based computer interfaces, client-facing web services,web servers that provide pages to web clients, etc.) for controlling,viewing, or otherwise interacting with HVAC system 100, its subsystems,and/or devices. Client device 368 may be a computer workstation, aclient terminal, a remote or local interface, or any other type of userinterface device. Client device 368 may be a stationary terminal or amobile device. For example, client device 368 may be a desktop computer,a computer server with a user interface, a laptop computer, a tablet, asmartphone, a PDA, or any other type of mobile or non-mobile device.Client device 368 may communicate with BMS controller 366 and/or AHUcontroller 330 via communications link 372.

Building Management Systems

Referring now to FIG. 4, a block diagram of a building management system(BMS) 400 is shown, according to some embodiments. BMS 400 may beimplemented in building 10 to automatically monitor and control variousbuilding functions. BMS 400 is shown to include BMS controller 366 and aplurality of building subsystems 428. Building subsystems 428 are shownto include a building electrical subsystem 434, an informationcommunication technology (ICT) subsystem 436, a security subsystem 438,a HVAC subsystem 440, a lighting subsystem 442, a lift/escalatorssubsystem 432, and a fire safety subsystem 430. In various embodiments,building subsystems 428 may include fewer, additional, or alternativesubsystems. For example, building subsystems 428 may also oralternatively include a refrigeration subsystem, an advertising orsignage subsystem, a cooking subsystem, a vending subsystem, a printeror copy service subsystem, or any other type of building subsystem thatuses controllable equipment and/or sensors to monitor or controlbuilding 10. In some embodiments, building subsystems 428 includewaterside system 200 and/or airside system 300, as described withreference to FIGS. 2-3.

Each of building subsystems 428 may include any number of devices,controllers, and connections for completing its individual functions andcontrol activities. HVAC subsystem 440 may include many of the samecomponents as HVAC system 100, as described with reference to FIGS. 1-3.For example, HVAC subsystem 440 may include a chiller, a boiler, anynumber of air handling units, economizers, field controllers,supervisory controllers, actuators, temperature sensors, and otherdevices for controlling the temperature, humidity, airflow, or othervariable conditions within building 10. Lighting subsystem 442 mayinclude any number of light fixtures, ballasts, lighting sensors,dimmers, or other devices configured to controllably adjust the amountof light provided to a building space. Security subsystem 438 mayinclude occupancy sensors, video surveillance cameras, digital videorecorders, video processing servers, intrusion detection devices, accesscontrol devices and servers, or other security-related devices.

Still referring to FIG. 4, BMS controller 366 is shown to include acommunications interface 407 and a BMS interface 409. Interface 407 mayfacilitate communications between BMS controller 366 and externalapplications (e.g., monitoring and reporting applications 422,enterprise control applications 426, remote systems and applications444, applications residing on client devices 448, etc.) for allowinguser control, monitoring, and adjustment to BMS controller 366 and/orsubsystems 428. Interface 407 may also facilitate communications betweenBMS controller 366 and client devices 448. BMS interface 409 mayfacilitate communications between BMS controller 366 and buildingsubsystems 428 (e.g., HVAC, lighting security, lifts, powerdistribution, business, etc.).

Interfaces 407, 409 may be or include wired or wireless communicationsinterfaces (e.g., jacks, antennas, transmitters, receivers,transceivers, wire terminals, etc.) for conducting data communicationswith building subsystems 428 or other external systems or devices. Invarious embodiments, communications via interfaces 407, 409 may bedirect (e.g., local wired or wireless communications) or via acommunications network 446 (e.g., a WAN, the Internet, a cellularnetwork, etc.). For example, interfaces 407, 409 may include an Ethernetcard and port for sending and receiving data via an Ethernet-basedcommunications link or network. In another example, interfaces 407, 409may include a Wi-Fi transceiver for communicating via a wirelesscommunications network. In another example, one or both of interfaces407, 409 may include cellular or mobile phone communicationstransceivers. In one embodiment, communications interface 407 is a powerline communications interface and BMS interface 409 is an Ethernetinterface. In other embodiments, both communications interface 407 andBMS interface 409 are Ethernet interfaces or are the same Ethernetinterface.

Still referring to FIG. 4, BMS controller 366 is shown to include aprocessing circuit 404 including a processor 406 and memory 408.Processing circuit 404 may be communicably connected to BMS interface409 and/or communications interface 407 such that processing circuit 404and the various components thereof may send and receive data viainterfaces 407, 409. Processor 406 may be implemented as a generalpurpose processor, an application specific integrated circuit (ASIC),one or more field programmable gate arrays (FPGAs), a group ofprocessing components, or other suitable electronic processingcomponents.

Memory 408 (e.g., memory, memory unit, storage device, etc.) may includeone or more devices (e.g., RAM, ROM, Flash memory, hard disk storage,etc.) for storing data and/or computer code for completing orfacilitating the various processes, layers and modules described in thepresent application. Memory 408 may be or include volatile memory ornon-volatile memory. Memory 408 may include database components, objectcode components, script components, or any other type of informationstructure for supporting the various activities and informationstructures described in the present application. According to someembodiments, memory 408 is communicably connected to processor 406 viaprocessing circuit 404 and includes computer code for executing (e.g.,by processing circuit 404 and/or processor 406) one or more processesdescribed herein.

In some embodiments, BMS controller 366 is implemented within a singlecomputer (e.g., one server, one housing, etc.). In various otherembodiments BMS controller 366 may be distributed across multipleservers or computers (e.g., that may exist in distributed locations).Further, while FIG. 4 shows applications 422 and 426 as existing outsideof BMS controller 366, in some embodiments, applications 422 and 426 maybe hosted within BMS controller 366 (e.g., within memory 408).

Still referring to FIG. 4, memory 408 is shown to include an enterpriseintegration layer 410, an automated measurement and validation (AM&V)layer 412, a demand response (DR) layer 414, a fault detection anddiagnostics (FDD) layer 416, an integrated control layer 418, and abuilding subsystem integration layer 420. Layers 410-420 may beconfigured to receive inputs from building subsystems 428 and other datasources, determine optimal control actions for building subsystems 428based on the inputs, generate control signals based on the optimalcontrol actions, and provide the generated control signals to buildingsubsystems 428. The following paragraphs describe some of the generalfunctions performed by each of layers 410-420 in BMS 400.

Enterprise integration layer 410 may be configured to serve clients orlocal applications with information and services to support a variety ofenterprise-level applications. For example, enterprise controlapplications 426 may be configured to provide subsystem-spanning controlto a graphical user interface (GUI) or to any number of enterprise-levelbusiness applications (e.g., accounting systems, user identificationsystems, etc.). Enterprise control applications 426 may also oralternatively be configured to provide configuration GUIs forconfiguring BMS controller 366. In yet other embodiments, enterprisecontrol applications 426 may work with layers 410-420 to optimizebuilding performance (e.g., efficiency, energy use, comfort, or safety)based on inputs received at interface 407 and/or BMS interface 409.

Building subsystem integration layer 420 may be configured to managecommunications between BMS controller 366 and building subsystems 428.For example, building subsystem integration layer 420 may receive sensordata and input signals from building subsystems 428 and provide outputdata and control signals to building subsystems 428. Building subsystemintegration layer 420 may also be configured to manage communicationsbetween building subsystems 428. Building subsystem integration layer420 translate communications (e.g., sensor data, input signals, outputsignals, etc.) across a plurality of multi-vendor/multi-protocolsystems.

Demand response layer 414 may be configured to optimize resource usage(e.g., electricity use, natural gas use, water use, etc.) and/or themonetary cost of such resource usage in response to satisfy the demandof building 10. The optimization may be based on time-of-use prices,curtailment signals, energy availability, or other data received fromutility providers, distributed energy generation systems 424, fromenergy storage 427 (e.g., hot TES 242, cold TES 244, etc.), or fromother sources. Demand response layer 414 may receive inputs from otherlayers of BMS controller 366 (e.g., building subsystem integration layer420, integrated control layer 418, etc.). The inputs received from otherlayers may include environmental or sensor inputs such as temperature,carbon dioxide levels, relative humidity levels, air quality sensoroutputs, occupancy sensor outputs, room schedules, and the like. Theinputs may also include inputs such as electrical use (e.g., expressedin kWh), thermal load measurements, pricing information, projectedpricing, smoothed pricing, curtailment signals from utilities, and thelike.

According to some embodiments, demand response layer 414 includescontrol logic for responding to the data and signals it receives. Theseresponses may include communicating with the control algorithms inintegrated control layer 418, changing control strategies, changingsetpoints, or activating/deactivating building equipment or subsystemsin a controlled manner. Demand response layer 414 may also includecontrol logic configured to determine when to utilize stored energy. Forexample, demand response layer 414 may determine to begin using energyfrom energy storage 427 just prior to the beginning of a peak use hour.

In some embodiments, demand response layer 414 includes a control moduleconfigured to actively initiate control actions (e.g., automaticallychanging setpoints) which minimize energy costs based on one or moreinputs representative of or based on demand (e.g., price, a curtailmentsignal, a demand level, etc.). In some embodiments, demand responselayer 414 uses equipment models to determine an optimal set of controlactions. The equipment models may include, for example, thermodynamicmodels describing the inputs, outputs, and/or functions performed byvarious sets of building equipment. Equipment models may representcollections of building equipment (e.g., subplants, chiller arrays,etc.) or individual devices (e.g., individual chillers, heaters, pumps,etc.).

Demand response layer 414 may further include or draw upon one or moredemand response policy definitions (e.g., databases, XML files, etc.).The policy definitions may be edited or adjusted by a user (e.g., via agraphical user interface) so that the control actions initiated inresponse to demand inputs may be tailored for the user's application,desired comfort level, particular building equipment, or based on otherconcerns. For example, the demand response policy definitions mayspecify which equipment may be turned on or off in response toparticular demand inputs, how long a system or piece of equipment shouldbe turned off, what setpoints may be changed, what the allowable setpoint adjustment range is, how long to hold a high demand setpointbefore returning to a normally scheduled setpoint, how close to approachcapacity limits, which equipment modes to utilize, the energy transferrates (e.g., the maximum rate, an alarm rate, other rate boundaryinformation, etc.) into and out of energy storage devices (e.g., thermalstorage tanks, battery banks, etc.), and when to dispatch on-sitegeneration of energy (e.g., via fuel cells, a motor generator set,etc.).

Integrated control layer 418 may be configured to use the data input oroutput of building subsystem integration layer 420 and/or demandresponse layer 414 to make control decisions. Due to the subsystemintegration provided by building subsystem integration layer 420,integrated control layer 418 may integrate control activities of thesubsystems 428 such that the subsystems 428 behave as a singleintegrated supersystem. In some embodiments, integrated control layer418 includes control logic that uses inputs and outputs from a pluralityof building subsystems to provide greater comfort and energy savingsrelative to the comfort and energy savings that separate subsystemscould provide alone. For example, integrated control layer 418 may beconfigured to use an input from a first subsystem to make anenergy-saving control decision for a second subsystem. Results of thesedecisions may be communicated back to building subsystem integrationlayer 420.

Integrated control layer 418 is shown to be logically below demandresponse layer 414. Integrated control layer 418 may be configured toenhance the effectiveness of demand response layer 414 by enablingbuilding subsystems 428 and their respective control loops to becontrolled in coordination with demand response layer 414. Thisconfiguration may advantageously reduce disruptive demand responsebehavior relative to conventional systems. For example, integratedcontrol layer 418 may be configured to assure that a demandresponse-driven upward adjustment to the setpoint for chilled watertemperature (or another component that directly or indirectly affectstemperature) does not result in an increase in fan energy (or otherenergy used to cool a space) that would result in greater total buildingenergy use than was saved at the chiller.

Integrated control layer 418 may be configured to provide feedback todemand response layer 414 so that demand response layer 414 checks thatconstraints (e.g., temperature, lighting levels, etc.) are properlymaintained even while demanded load shedding is in progress. Theconstraints may also include setpoint or sensed boundaries relating tosafety, equipment operating limits and performance, comfort, fire codes,electrical codes, energy codes, and the like. Integrated control layer418 is also logically below fault detection and diagnostics layer 416and automated measurement and validation layer 412. Integrated controllayer 418 may be configured to provide calculated inputs (e.g.,aggregations) to these higher levels based on outputs from more than onebuilding subsystem.

Automated measurement and validation (AM&V) layer 412 may be configuredto verify that control strategies commanded by integrated control layer418 or demand response layer 414 are working properly (e.g., using dataaggregated by AM&V layer 412, integrated control layer 418, buildingsubsystem integration layer 420, FDD layer 416, or otherwise). Thecalculations made by AM&V layer 412 may be based on building systemenergy models and/or equipment models for individual BMS devices orsubsystems. For example, AM&V layer 412 may compare a model-predictedoutput with an actual output from building subsystems 428 to determinean accuracy of the model.

Fault detection and diagnostics (FDD) layer 416 may be configured toprovide on-going fault detection for building subsystems 428, buildingsubsystem devices (i.e., building equipment), and control algorithmsused by demand response layer 414 and integrated control layer 418. FDDlayer 416 may receive data inputs from integrated control layer 418,directly from one or more building subsystems or devices, or fromanother data source. FDD layer 416 may automatically diagnose andrespond to detected faults. The responses to detected or diagnosedfaults may include providing an alert message to a user, a maintenancescheduling system, or a control algorithm configured to attempt torepair the fault or to work-around the fault.

FDD layer 416 may be configured to output a specific identification ofthe faulty component or cause of the fault (e.g., loose damper linkage)using detailed subsystem inputs available at building subsystemintegration layer 420. In other exemplary embodiments, FDD layer 416 isconfigured to provide “fault” events to integrated control layer 418which executes control strategies and policies in response to thereceived fault events. According to some embodiments, FDD layer 416 (ora policy executed by an integrated control engine or business rulesengine) may shut-down systems or direct control activities around faultydevices or systems to reduce energy waste, extend equipment life, orassure proper control response.

FDD layer 416 may be configured to store or access a variety ofdifferent system data stores (or data points for live data). FDD layer416 may use some content of the data stores to identify faults at theequipment level (e.g., specific chiller, specific AHU, specific terminalunit, etc.) and other content to identify faults at component orsubsystem levels. For example, building subsystems 428 may generatetemporal (i.e., time-series) data indicating the performance of BMS 400and the various components thereof. The data generated by buildingsubsystems 428 may include measured or calculated values that exhibitstatistical characteristics and provide information about how thecorresponding system or process (e.g., a temperature control process, aflow control process, etc.) is performing in terms of error from itssetpoint. These processes may be examined by FDD layer 416 to exposewhen the system begins to degrade in performance and alert a user torepair the fault before it becomes more severe.

Estimating Flow Rate Values of a Valve

Referring to FIG. 5, one non-limiting example of a flow rate sensorworking range is provided. As shown by the graph 500, flow rate valuesbelow the minimum flow rate threshold (y_(min)) read as 0. Conversely,flow rate values above the maximum rating of the flow sensor (y_(max))may read as saturations at the maximum flow. In some situations, thebehavior of the flow rate sensors outside of the working range mayaffect the ability of a flow controller to reach desired flow setpoints.

Referring now to FIG. 6, a block diagram of a system 600 including anactuator 602, a valve device 604, and a controller 614 is shown,according to some embodiments. System 600 may be implemented in HVACsystem 100, waterside system 200, airside system 300, or BMS 400, asdescribed with reference to FIGS. 1-4. As shown, actuator 602 may becoupled to valve device 604. For example, actuator 602 may be a damperactuator, a fan actuator, a pump actuator, or any other type of actuatorthat may be used in an HVAC system or BMS. In various embodiments,actuator 602 may be a linear actuator (e.g., a linear proportionalactuator), a non-linear actuator, a spring return actuator, or anon-spring return actuator.

Valve device 604 may be any type of control device configured to controlan environmental parameter in an HVAC system, including a 2-way or 3-waytwo position electric motorized valve, a ball isolation value, afloating point control valve, an adjustable flow control device, or amodulating control valve. In some embodiments, valve device 604 mayregulate the flow of fluid through a conduit, pipe, or tube (e.g.,conduit 612) in a waterside system (e.g., waterside system 200, shown inFIG. 2). Conduit 512 may include upstream conduit section 606 anddownstream conduit section 608. In other embodiments, valve 604 mayregulate the flow of air through a duct in an airside system (e.g.,airside system 300, shown in FIG. 3).

In some embodiments, actuator 602 and valve device 604 may be locatedwithin a common integrated device chassis or housing. In short, actuator602 and valve device 604 may not be packaged as separate devices, but asa single device. However, in some embodiments, actuator 602 and valvedevice 604 may be packaged as separate devices that may be communicablycoupled via a wire or a wireless connection.

Still referring to FIG. 6, flow sensor 610 is shown to be disposedwithin downstream conduit section 608. Flow sensor 610 may be configuredto measure the flow rate or velocity of fluid passing through conduit612, and more specifically, the flow rate of fluid exiting valve 604.Flow sensor 610 may be any type of device (e.g., ultrasonic detector,paddle-wheel sensor, pitot tube, drag-force flowmeter) configured tomeasure the flow rate or velocity using any applicable flow sensingmethod.

In some embodiments, flow sensor 610 may be a heated thermistor flowsensor that operates according to the principles of King's Law.According to King's Law, the heat transfer from a heated object exposedto a moving fluid is a function of the velocity of the fluid. King's Lawdevices have several features, including very high sensitivity at lowflow rates and measurement of the fluid temperature (which may be usefulfor fault detection and control purposes), although they have decreasedsensitivity at high flow rates.

In other embodiments, flow sensor 610 may be a vortex-shedding flowmeterconfigured to determine the fluid flow rate by calculating the Strouhalnumber. The Strouhal number is a dimensionless value useful forcharacterizing oscillating flow dynamics. A vortex-shedding flowmetermeasures the flow rate via acoustic detection of cortices in fluidcaused when the fluid flows past a cylindrically-shaped obstruction. Thevibrating frequency of the vortex shedding is correlated to the flowvelocity. Vortex-shedding flowmeters generally have good sensitivityover a range of flow rates, although they require a minimum flow rate inorder to be operational.

In some embodiments, flow sensor 610 may be communicably coupled toactuator 602. For example, flow sensor 610 may be coupled via wired orwireless connection to a controller 614 of system 600 for the purpose oftransmission of flow rate measurements. In various embodiments, flowrate data signals may be used by the controller of device 600 todetermine control operations for actuator 602 and/or valve 604. Infurther embodiments, flow sensor 610 may be disposed within valve 604 tomeasure the rate of fluid flow before the fluid exits valve 604. Whenflow sensor 610 is located within valve 604, flow sensor 610 mayadditionally function as a fault detection mechanism for system 600. Forexample, when debris becomes lodged in actuator 602 or valve 604, flowthrough valve 604 may be significantly reduced. This reduction in flowmay occur because the components of actuator 602 cannot freely operatevalve 604, or because the debris within valve 604 obstructs flow throughconduit 612.

Still referring to FIG. 6, pressure sensors 616 a, 616 b are shown to bedisposed within conduit 612. Pressure sensors 616 a, 616 b may beconfigured to measure pressure within conduit 612. In some embodiments,a differential pressure (Δp) may be calculated using a pressuremeasurement from pressure sensor 616 a and a separate pressuremeasurement from pressure sensor 616 b. As one example, pressure sensor616 a may be disposed within upstream conduit section 606 and may beconfigured to measure a pressure upstream of valve 604. Conversely,pressure sensor 616 b may be disposed within downstream conduit section608 and may be configured to measure a pressure downstream of valve 604.

In some embodiments, pressure sensors 616 a, 616 b may be communicablycoupled to actuator 602. For example, pressure sensors 616 a, 616 b maybe coupled via wired or wireless connection to a controller 614 ofsystem 600 for the purpose of transmission of pressure measurements. Invarious embodiments, Δp data signals may be used by controller 614 todetermine control operations for actuator 602 and/or valve 604.

As shown by FIG. 6, controller 614 may receive input signals such asflow measurements from flow sensor 610 and Δp measurements from thepressure sensors 616 a, 616 b. Additionally, controller 614 may receiveposition feedback signals from actuator 602. The position feedbacksignals may be used by controller 614 to determine control operationsfor actuator 602 and/or valve 604. Controller 614 may provide a controlsignal to actuator 602. The control signal may be used to operateactuator 602. The control signal may be determined by the controllerusing various methods. In some situations, the control signal may bedetermined based on a combination of inputs (e.g., flow measurements,position feedback, Δp measurements). In some situations, the controlsignal may be at least partially determined by known properties and/orexperimentally determined values associated with valve 604.

Referring now to FIG. 7, a block diagram of another system 700 is shown,according to some embodiments. System 700 may be used in HVAC system100, waterside system 200, airside system 300, or BMS 400, as describedwith reference to FIGS. 1-4. System 700 may represent an alternateconfiguration of system 600. For example, controller 714 may becontained within actuator 702. Specifically, controller 714 and actuator702 may be packaged and installed as a single component. As shown,controller 714 receives flow measurements from flow sensor 710.

System 700 may be such that valve device 704 may regulate the flow offluid through a conduit, pipe, or tube (e.g., conduit 712) in awaterside system (e.g., waterside system 200, shown in FIG. 2). Conduit712 may include upstream conduit section 706 and downstream conduitsection 708. Flow sensor 710 may be disposed within downstream conduitsection 708. Valve 704 may function similarly to valve 604, aspreviously described.

Examples of “smart actuators” including a controller which can be usedin system 600 and/or system 700 are described in detail in U.S. Pat. No.9,746,199 issued on Aug. 29, 2017 and entitled “Integrated SmartActuator and Valve Device.” The entire disclosure of this patent isincorporated by reference herein.

Referring to FIG. 8, graph 800 illustrates an example of the flow ratemeasured by a flow rate sensor for a given opening of a valve. Line 802represents the flow rate values that the flow rate sensor may typicallyoutput. As shown, the flow measured above y_(min) behaves exponentiallywith respect to the valve opening and flows below y_(min) are read as 0by the flow rate sensor. In contrast, line 806 shows what the flow ratevalues would be if the flow rate sensor could read continuously belowy_(min).

Still referring to FIG. 8, if the flow rate sensor were able to read anyflow greater than zero, it would read a flow of y_(i) gpm when the valveopening is x_(i) %; instead, it reads a zero gpm value since the valveopening x_(i) is below the x_(min) value that produces a readable flow.This nonlinearity may be compensated by estimating the value of y_(i)for a given x_(i). According to one embodiment of the presentdisclosure, a line may be drawn between the origin and the point(x_(min), y_(min)) (e.g., line 804). The line may then be used tocalculate an estimated flow ŷ_(f) (i.e. a corrected flow) for thecurrent valve opening.

In other embodiments, a function may be determined based on the originand the point (x_(min), y_(min)). The function may be, for example,quadratic, exponential, cubic, or an n^(th) order polynomial. Thefunction may be based on experimental data and analysis.

Referring now to FIG. 9, a block diagram illustrating controller 900 indetail is shown, according to one embodiment. Controller 900 can be usedas controller 614 in system 600 and/or controller 714 in system 700.Controller 900 is shown to include a communications interface 908 and aprocessing circuit 902. Communications interface 908 may include wiredor wireless interfaces (e.g., jacks, antennas, transmitters, receivers,transceivers, wire terminals, etc.) for conducting data communicationswith various systems, devices, or networks. For example, communicationsinterface 908 may include an Ethernet card and port for sending andreceiving data via an Ethernet-based communications network and/or aWiFi transceiver for communicating via a wireless communicationsnetwork. Communications interface 908 may be configured to communicatevia local area networks or wide area networks (e.g., the Internet, abuilding WAN, etc.) and may use a variety of communications protocols(e.g., BACnet, IP, LON, etc.).

Communications interface 908 may be a network interface configured tofacilitate electronic data communications between controller 900 andvarious external systems or devices (e.g., actuator 910, flow ratesensor 912, etc.). Controller 900 may receive position feedback fromactuator 910 and measured flow rates (y_(f)) from flow rate sensor 912.Controller 900 may be configured to output a corrected flow rate (ŷ_(f))to feedback controller 920, as well as receive a control signal fromfeedback controller 920.

Processing circuit 902 is shown to include a processor 904 and memory906. Processor 904 may be a general purpose or specific purposeprocessor, an application specific integrated circuit (ASIC), one ormore field programmable gate arrays (FPGAs), a group of processingcomponents, or other suitable processing components. Processor 904 maybe configured to execute computer code or instructions stored in memory906 or received from other computer readable media (e.g., CDROM, networkstorage, a remote server, etc.).

Memory 906 may include one or more devices (e.g., memory units, memorydevices, storage devices, etc.) for storing data and/or computer codefor completing and/or facilitating the various processes described inthe present disclosure. Memory 906 may include random access memory(RAM), read-only memory (ROM), hard drive storage, temporary storage,non-volatile memory, flash memory, optical memory, or any other suitablememory for storing software objects and/or computer instructions. Memory906 may include database components, object code components, scriptcomponents, or any other type of information structure for supportingthe various activities and information structures described in thepresent disclosure. Memory 906 may be communicably connected toprocessor 904 via processing circuit 902 and may include computer codefor executing (e.g., by processor 904) one or more processes describedherein.

Still referring to FIG. 9, controller 900 is shown to include athreshold calculator 916. Threshold calculator 916 is shown receivingthe measured flow rate (y_(f)) from flow rate sensor 912. Additionally,threshold calculator 916 may receive a valve opening position (x_(i))from a position detector 914. Threshold calculator 916 may calculate aminimum valve position threshold (x_(min)) and/or a minimum flow ratethreshold (y_(min)) for a given valve, in accordance with the methodsdescribed herein. x_(min) and y_(min) may be provided as an input to aflow rate estimator 918.

Flow rate estimator 918 is shown receiving x_(min) and y_(min) fromthreshold calculator 916, as well as the valve opening position (x_(i))from position detector 914. Flow rate estimator 918 may be configured touse the inputs x_(min), y_(min), and x_(i) to calculate a corrected flowrate (ŷ_(f)), in accordance with the methods described by performing anyof steps 1110, 1212, 1912 described in detail with reference to FIGS.11, 12, and 19. ŷ_(f) may be provided as an input to feedback controller920.

Feedback controller 920 is shown receiving ŷ_(f) from flow rateestimator 918. Based on ŷ_(f), feedback controller 920 may determine acontrol signal (e.g., an associated output voltage) that may be providedto actuator 910 to further open or close the associated valve opening.The control signal may be provided as an input to actuator 910, and/orto position detector 914.

Providing the control signal from feedback controller 920 to positiondetector 914 may provide a distinct benefit. As will be discussed belowin detail, the methods described herein use the valve opening position(x_(i)) in the calculations to determine ŷ_(f). The valve openingposition (x_(i)) may be provided by the position of the valve actuator(e.g., actuator 910). However, there may be valves that are unable toexpose the actuator position to position detector 914. In thesesituations, it may be beneficial to use the control signal directly fromfeedback controller 920 as a proxy for x_(i). Since the valve shouldeventually open or close according to the value of the control signal,as provided by feedback controller 920, it may be beneficial to use thecontrol signal when the actuator position cannot be exposed, or when itis otherwise difficult to use.

Still referring to FIG. 9, position detector 914 is shown receiving thecontrol signal from feedback controller 920, and the position feedbackfrom actuator 910. In some embodiments, position detector 914 may onlyreceive one of the position feedback or the control signal, for reasonsdiscussed in the preceding paragraphs. In other embodiments, positiondetector 914 may receive both the position feedback and the controlsignal as inputs. Position detector 914 is configured to calculate avalve opening position x_(i) using position feedback and/or the controlsignal. Position detector 914 may provide x_(i) to both thresholdcalculator 916 and flow rate estimator 918.

Referring now to FIG. 10, a block diagram illustrating controller 1000in detail is shown, according to one embodiment. Controller 1000 isshown to include a communications interface 1008, processing circuit1002, processor 1004, and memory 1006. In some embodiments, controller1000 may be similar to controller 900, as described above. In someembodiments, communications interface 1008 may be similar tocommunications interface 908, as described above. In some embodiments,processing circuit 1002 may be similar to processing circuit 902, asdescribed above. In some embodiments, processor 1004 may be similar toprocessor 904. In some embodiments, memory 1006 may be similar to memory906.

Communications interface 1008 may be a network interface configured tofacilitate electronic data communications between controller 1000 andvarious external systems or devices (e.g., actuator 1010, flow ratesensor 1024, pressure sensor 1012, etc.). Controller 1000 may receivemeasured flow rates (y_(f)) from flow rate sensor 1024 and change inpressure (Δp) from pressure sensor 1012. Controller 1000 may beconfigured to output a corrected flow rate (ŷ_(f)) to feedbackcontroller 1022.

Pressure sensor 1012 may be configured to measure a differentialpressure (Δp) across the valve. This may be done via a plurality ofsensors (e.g., as described by FIG. 6). By using Δp as an input, thecorrected flow rate (ŷ_(f)) may be calculated. Advantageously, thissystem and associated methods do not rely on determining a valve openingposition (x_(i)); in some situations, determining a valve openingposition may not be possible or may be difficult. By using Δp as aninput, the valve opening position does not need to be determined.

Still referring to FIG. 10, controller 1000 is shown to include athreshold calculator 1026. Threshold calculator 1026 is shown receivingthe measured flow rate (y_(f)) from flow rate sensor 1024. Thresholdcalculator 1026 may calculate a minimum valve position threshold(x_(min)) and/or a minimum flow rate threshold (y_(min)) for a givenvalve, in accordance with the methods described herein. x_(min) andy_(min) may be provided as an input to a flow rate estimator 1020.

In some embodiments, the values of x_(min) and y_(min) may be knownbased on valve identification information. Accordingly, thresholdcalculator 1026 may not be used to calculate x_(min) and y_(min). Inthese situations, valve equation identifier 1016 may provide x_(min) andy_(min) to flow rate estimator 1020.

Controller 1000 is shown to include a valve identifier 1014, whichoutputs a valve ID to valve equation identifier 1016. The valveidentifier 1014 may read the valve ID from memory 1006. Alternatively,valve identifier 1014 may utilize user input via communicationsinterface 1008 to determine the proper valve ID.

Still referring to FIG. 10, controller 1000 is shown to include valveequation identifier 1016. Commonly, different valve types have differentcorresponding valve equations that may be used in the calculation ofvarious system variables. As shown, the valve equations may be stored ina valve equation database 1018. Alternatively, the valve equations maybe stored in a look-up table. The valve equation database 1018 orlook-up table may be stored in the controller memory 1006, or may bestored externally and accessed by controller 1000. Using the valve IDinput, valve equation identifier 1016 determines and outputs a valveequation. As discussed above, valve equation identifier 1016 may alsooutput known values for x_(min) and y_(min). The valve equation andx_(min) and y_(min) may be provided as inputs to flow rate estimator1020.

Flow rate estimator 1020 is shown receiving x_(min) and y_(min) fromeither threshold calculator 1026 or valve equation identifier 1016.Additionally, flow rate estimator 1020 is shown receiving a valveequation from valve equation identifier 1016, and Δp from pressuresensor 1012. Flow rate estimator 1020 is configured to use the inputsx_(min), y_(min), the valve equation, and Δp to calculate a correctedflow rate (ŷ_(f)), in accordance with the methods described byperforming any of steps 1110, 1212, 1912 described in detail withreference to FIGS. 11, 12, and 19. ŷ_(f) may be provided as an input tofeedback controller 1022.

Feedback controller 1022 is shown receiving ŷ_(f) from flow rateestimator 1020. Based on ŷ_(f), feedback controller 920 may determine anassociated output voltage that may be provided to actuator 1010 tofurther open or close the associated valve opening.

In some embodiments, actuators 1010, 910, 602 may function similarly. Insome embodiments, actuators 1010, 910, 702 may function similarly. Insome embodiments, controllers 614, 900, 1000, 714 may functionsimilarly. In some embodiments, flow sensors 710, 912, 610, 1024 mayfunction similarly. In some embodiments, pressure sensor 1012 mayincorporate the functionality of multiple pressure sensors (e.g.,pressure sensors 616 a, 616 b).

Referring now to FIG. 11, a flowchart of a flow rate correction method1100 which may be performed by controller 900, is shown. Alternatively,the flow rate correction method 1100 may be performed by a differentcontroller. Method 1100 is shown to include measuring a flow rate, y_(f)(step 1102). The measuring of the flow rate may be done using any of theflow rate sensors previously described. The measured flow rate (y_(f))is then compared to a predetermined flow rate value (step 1104). In someembodiments, the predetermined flow rate value is zero.

If the measured flow rate (y_(f)) is not equal to the predetermined flowrate value (i.e., the result of step 1104 is “no”), the measured flowrate (y_(f)) may then be used to control a valve operation (step 1114).This may occur, for example, when the measured flow rate (y_(f)) isnon-zero. Alternatively, if the measured flow rate (y_(f)) is equal tothe predetermined flow rate value (i.e., the result of step 1104 is“yes”), a minimum valve position threshold (x_(min)) may then bedetermined (step 1106). This may occur, for example, when the measuredflow rate (y_(f)) is equal to zero. Additionally, a minimum flow ratethreshold (y_(min)) that corresponds to x_(min) may then be determined(step 1108).

Once x_(min) and y_(min) are determined, a corrected flow rate (y_(f))may be calculated using x_(min), y_(min), and a valve positionindication (step 1110). In some embodiments, the valve positionindication may be a change in pressure through the valve (Δp). In otherembodiments, the valve position indication may be a valve openingposition (x_(i)). In some embodiments, the valve position indication maycorrespond with a value other than Δp or x_(i), depending on the desiredimplementation of method 1100. A valve operation may then be controlledusing ŷ_(f) (step 1112).

In some embodiments, the flow rate y_(f) may be estimated as {tilde over(y)}_(f)=g(x_(i), x_(min), y_(min)). In some embodiments, a sensoroutput many utilize a function that outputs the measured flow rate if itis non-zero, or the estimated flow rate {tilde over (y)}_(f) otherwise.As one non-limiting example, the sensor may implement the function shownby Equation 1:

$\begin{matrix}{{\hat{y}}_{f} = \left\{ \begin{matrix}{y_{f},} & {{{if}\mspace{14mu} y_{f}} \neq 0} \\{{\overset{\sim}{y}}_{f},} & {otherwise}\end{matrix} \right.} & (1)\end{matrix}$The interpolation function g( ) may have many different forms, and arenot limited to the forms discussed herein.

In some embodiments, g( ) may be a polynomial function. Further, in someembodiments, the polynomial function may have the form

${g\left( {x_{i},x_{\min},y_{\min}} \right)} = {\frac{y_{\min}}{x_{\min}^{n}}x_{i}^{n}}$where n may be the degree of the polynomial function. Accordingly, insome embodiments, the interpolation type may be selected by choosing avalue of n. In one non-limiting embodiment, linear interpolation may beimplemented using n=1. In another non-limiting embodiment, quadraticinterpolation may be implemented using n=2. In some situations, it maybe beneficial to use a cubic interpolation, where n=3.

In some embodiments, g( ) may be an exponential function. Further, insome embodiments, the polynomial function may have the form g(x_(i),x_(min), y_(min))=y_(min)b^(−x) ^(min) b^(x) ^(i) where b may be achosen constant. In some situations, it may be beneficial to use themathematical constant e=2.718. In some embodiments, a different valuefor b may be used.

In some embodiments, g( ) may include a spline interpolation (e.g.,using a piecewise polynomial). In certain situations, it may bebeneficial to use a spline interpolation in order to minimize anyinterpolation error.

In some embodiments, the corrected flow rate (ŷ_(f)) may be calculatedby performing a linear interpolation between the predetermined flow ratevalue and the minimum flow rate threshold y_(min) as a function of theindication of valve opening position. The linear interpolation mayinclude calculating a slope

$\frac{y_{\min}}{x_{\min}}$and multiplying the slope

$\frac{y_{\min}}{x_{\min}}$by an indication of valve position to calculate the corrected flow rateŷ_(f).

As one non-limiting example, a function may be used. As one non-limitingexample, if the measured flow rate is nonzero, the corrected flow ratemay be equal to the measured flow rate. If the measured flow rate iszero, the corrected flow rate may be equal to the calculated slopemultiplied by the indication of valve position.

Referring to FIG. 12, a flowchart of another flow rate correction method1200, which may be performed by controller 1000, is shown.Alternatively, the flow rate correction method 1200 may be performed bya different controller. Method 1200 is shown to include measuring a flowrate, y_(f) (step 1202). The measuring of the flow rate may be doneusing any of the flow rate sensors, as described above. The measuredflow rate (y_(f)) is then compared to a predetermined flow rate value(step 1204). In some embodiments, the predetermined flow rate value iszero.

If the measured flow rate (y_(f)) is not equal to the predetermined flowrate value (i.e., the result of step 1204 is “no”), the measured flowrate (y_(f)) may then be used to control a valve operation (step 1216).This may occur, for example, when the measured flow rate (y_(f)) isnon-zero. Alternatively, if the measured flow rate (y_(f)) is equal tothe predetermined flow rate value (i.e., the result of step 1204 is“yes”), a change in pressure (Δp) across the valve may be measured (step1206). This may occur, for example, when the measured flow rate (y_(f))is equal to zero. Δp may be measured using pressure sensors, aspreviously described.

Still referring to method 1200, a valve type may be identified (step1208). The valve type may be stored in a memory corresponding to thecontroller. Using the valve type, corresponding valve equation(s) may bedetermined (step 1210). As discussed in relation to FIG. 10, the valveequations may be stored in a database or look-up table. The database orlook-up table may be stored in the controller memory, or may be storedexternally and accessed by the controller during step 1210. Using thechange in pressure (Δp) and the valve equation(s), a corrected flow rate(ŷ_(f)) may be calculated (step 1212). A valve operation may then becontrolled using ŷ_(f) (step 1214).

In some embodiments, an installed flow characteristic for a valve mayhave the form

$\begin{matrix}{{g\left( {x_{i},x_{\min},y_{\min}} \right)} = {C_{v}\sqrt{\Delta\; P}C_{v,i}^{inst}}} & (2) \\{with} & \; \\{C_{v,i}^{inst} = \sqrt{\frac{\;^{1}\text{/}_{N}}{\frac{1}{N} - 1 + \frac{1}{k_{i}^{2}}}}} & (3) \\{and} & \; \\{k_{i} = R^{x_{i} - 1}} & (4)\end{matrix}$

With respect to Equations 2-4, ΔP may be the pressure drop across thevalve, C_(v) may be the valve coefficient, N may correspond to the valveauthority, and R may be the valve rangeability. The terms C_(v), N, andR may be constant values. In some embodiments, the constant values maybe known from the valve and overall system design. In some embodiments,ΔP may be estimated from the flow measurements and the other knownvalues and parameters as:

$\begin{matrix}{\sqrt{\Delta\; P} = \frac{y_{\min}}{C_{v}C_{v,\min}^{inst}}} & (5) \\{and} & \; \\{C_{v,\min}^{inst} = \sqrt{\frac{\;^{1}\text{/}_{N}}{\frac{1}{N} - 1 + \frac{1}{k_{\min}^{2}}}}} & (6) \\{k_{\min} = R^{x_{\min} - 1}} & (7)\end{matrix}$

In some embodiments, the minimum valve opening (x_(min)) thatcorresponds to the minimum measurable flow y_(min) may not be known.Typically, x_(min) depends on the valve size and the pressure drop (Δp)across the valve. Accordingly, the present disclosure includes methodsfor estimating x_(min).

FIG. 8 shows that flow values are zero to the left of x_(min) andnon-zero to the right. This separation may help estimate the minimumvalve position threshold ({circumflex over (x)}_(min)). When the sensoroutput is zero, x_(min) may be the largest value that x_(i) can achieve.Accordingly, in some embodiments, this value may be estimated as{circumflex over (x)}_(min)=max({circumflex over (x)}_(min), x_(i)).

In contrast, when the sensor output is non-zero, x_(min) may be thesmallest of all possible values of x_(i). Accordingly, in someembodiments, this value may be estimated as {circumflex over(x)}_(min)=min({circumflex over (x)}_(min), x_(i)). In some embodiments,the value of {circumflex over (x)}_(min) may be updated when the sensoroutput changes. In some situations, the value of {circumflex over(x)}_(min) may be updated when the sensor output changes from zero to anon-zero value and/or from a non-zero value to zero.

In some embodiments, {circumflex over (x)}_(min) may be initialized to100. Pressure changes in the valve may change the value of x_(min). Asone non-limiting example, an increment in the pressure drop may reducethe actual value of x_(min), and a pressure reduction may result in alarger x_(min).

In some situations, noise in a flow sensor may affect the output of theflow controller, which may affect the estimated value {circumflex over(x)}_(min). Accordingly, in some embodiments, filtering {circumflex over(x)}_(min) may reduce the effect of noise.

In some embodiments, an exponentially weighted moving average (EWMA) maybe used to filter the value of {circumflex over (x)}_(min). In somesituations, {circumflex over (x)}_(min) may be filtered at each sampletime. Many other filtering techniques may be implemented, and an EWMA isdiscussed herein as a non-limiting example.

Using an EWMA, a filtered estimated minimum valve position threshold, x_(min), may be obtained:x _(min) =x _(min)+α({circumflex over (x)} _(min) −x _(min))  (8)a weight, α, may be chosen asα=e ^(−h/τ) ^(a)   (9)where h may be the sample rate of the flow controller, and τ_(a) may bethe time constant of the valve actuator. In some embodiments, thefiltered value may be initialized as x _(min)={circumflex over(x)}_(min).

In some embodiments, other methods may be used to estimate the minimumvalve position threshold ({circumflex over (x)}_(min)). In anotherembodiment, the separation of zero and non-zero sensor output value mayhelp estimate the minimum valve position threshold ({circumflex over(x)}_(min)). In the first case, {circumflex over (x)}_(min) may beestimated when the sensor output is zero; this calculated value may bereferred to as a first minimum valve position threshold, {circumflexover (x)}_(min,left). In the second case, {circumflex over (x)}_(min)may be estimated when the flow sensor output is non-zero; thiscalculated value may be referred to as a second minimum valve positionthreshold, {circumflex over (x)}_(min,right).

Referring now to FIG. 13, a flowchart of a method 1300 for estimating aminimum valve position threshold is shown, according to someembodiments. In some embodiments, method 1300 may be performed toaccomplish step 1106 of FIG. 11 (i.e. determining a minimum valveposition threshold, x_(min)). Method 1300 is shown to includedetermining a first minimum valve position threshold, {circumflex over(x)}_(min,left) (step 1302). A second minimum valve position threshold,{circumflex over (x)}_(min,right) may be determined (step 1304). Once{circumflex over (x)}_(min,left) {circumflex over (x)}min,right aredetermined, the values may be used to calculate an estimated minimumvalve position threshold, {circumflex over (x)}_(min) (step 1306). Forexample, the estimated minimum valve position threshold, {circumflexover (x)}_(min) can be set equal to the average of {circumflex over(x)}_(min,left) and {circumflex over (x)}_(min,right). The minimum valveposition threshold (x_(min)) may then be set as the estimated minimumvalve position threshold ({circumflex over (x)}_(min)) (step 1308). Insome embodiments, step 1306 may include averaging {circumflex over(x)}_(min,left) and {circumflex over (x)}_(min,right). In otherembodiments, {circumflex over (x)}_(min,left) and {circumflex over(x)}_(min,right) may be used to compute {circumflex over (x)}_(min)using different mathematical functions. Further, in some embodiments,{circumflex over (x)}_(min,left) and {circumflex over (x)}_(min,right)may be initialized at predetermined values.

Referring now to FIG. 14, a flowchart of a method 1400 for determining afirst minimum valve position threshold is shown. In some embodiments,method 1400 may be performed to accomplish step 1302 of FIG. 13 (i.e.determining a first minimum valve position threshold, {circumflex over(x)}_(min,left)) Method 1400 includes step 1402, where if the measuredflow rate (y_(f)) is not equal to the predetermined flow rate value(i.e. the result of step 1402 is “no”), then the first minimum valveposition threshold ({circumflex over (x)}_(min,left)) is set to 0 (step1404).

Alternatively, if the measured flow rate (y_(f)) is equal to thepredetermined flow rate value (i.e. the result of step 1402 is “yes”),then the valve position (x_(i)) is determined (step 1406). If x_(i) isgreater than the first minimum valve position threshold (i.e. the resultof step 1408 is “yes”), then the first minimum valve position threshold({circumflex over (x)}_(min,left)) is updated to equal the valveposition, x_(i) (step 1410). Alternatively, if x_(i) is less than thefirst minimum valve position threshold (i.e. the result of step 1408 is“no”), then the first minimum valve position threshold ({circumflex over(x)}_(min,left)) remains at its current value (step 1412).

Referring now to FIG. 15, a flowchart of a method 1500 for determining asecond minimum valve position threshold is shown. In some embodiments,method 1500 may be performed to accomplish step 1304 of FIG. 13 (i.e.determining a second minimum valve position threshold, {circumflex over(x)}_(min,right)). Method 1500 includes step 1502, where if the measuredflow rate (y_(f)) is equal to the predetermined flow rate value (i.e.the result of step 1502 is “yes”), then the second minimum valveposition threshold ({circumflex over (x)}_(min,right)) is set to 100 oranother large value (step 1504).

Alternatively, if the measured flow rate (y_(f)) is not equal to thepredetermined flow rate value (i.e. the result of step 1502 is “no”),then the valve position (x_(i)) is determined (step 1506). If x_(i) isless than the second minimum valve position threshold (i.e. the resultof step 1508 is “yes”), then the second minimum valve position threshold({circumflex over (x)}_(min,right)) is updated to equal the valveposition, x_(i) (step 1510). Alternatively, if x_(i) is greater than thesecond minimum valve position threshold (i.e. the result of step 1508 is“no”), then the second minimum valve position threshold ({circumflexover (x)}_(min,right)) remains at its current value (step 1512).

With reference to methods 1300, 1400, and 1500 (as shown in FIGS.13-15), for a constant pressure drop in a valve, {circumflex over(x)}_(min,right) and {circumflex over (x)}_(min,left) should be thesame, thus, the estimated minimum valve position threshold ({circumflexover (x)}_(min)) may be approximately equal to the actual minimum valveopening (x_(min)). However, if the pressure drop increases or decreasesin the valve, then {circumflex over (x)}_(min,right) and {circumflexover (x)}_(min,left) may be different.

For example, an increment in the pressure drop reduces the actual valueof x_(min). The reduction in x_(min) causes {circumflex over(x)}_(min,right) to decrease, but {circumflex over (x)}_(min,left)remains constant; this happens due to the setting of {circumflex over(x)}_(min,left) to the maximum of x_(i) and {circumflex over(x)}_(min,left). Conversely, a reduction in the pressure drop results ina larger x_(min), which increases the value of {circumflex over(x)}_(min,left) and keeps the value of {circumflex over (x)}_(min,right)constant; this happens due to the setting of {circumflex over(x)}_(min,right) to the minimum of x_(i) and {circumflex over(x)}_(min,right).

Due to the effect of pressure changes described in the precedingparagraphs, {circumflex over (x)}_(min) may be set equal to the averageof {circumflex over (x)}_(min,right) and {circumflex over(x)}_(min,left). By averaging {circumflex over (x)}_(min,right) and{circumflex over (x)}_(min,left), the effect of the pressure changes onthe estimation of the minimum valve position threshold is decreased.

In some situations, the minimum flow rate threshold (y_(min)) may not beavailable. Accordingly, the present disclosure includes a method forestimating y_(min).

Referring now to FIG. 16, a flowchart of a method 1600 for estimating aminimum flow rate threshold is shown. In some embodiments, method 1600may be performed to accomplish step 1108 of FIG. 11 (i.e. determining aminimum flow rate threshold, y_(min)). Method 1600 includes determininga maximum rating of a flow rate sensor, y_(max) (step 1602). In someembodiments, the maximum rating of the flow rate sensor may be known dueto the type of flow rate sensor. Once y_(max) is determined, anestimated minimum flow rate threshold (ŷ_(min))may be calculated usingthe maximum rating (step 1604). In some embodiments, ŷ_(min) may be setto a percentage of y_(max). In some embodiments, ŷ_(min) may be set toy_(max). Next, the minimum flow rate threshold (y_(min)) may be set tothe estimated minimum flow rate threshold (ŷ_(min)) (step 1606).

Initializing ŷ_(min) at 100% of the maximum sensor rating value providesa “worst case” estimate, since most of the minimum values are around 10%of the maximum sensor rating. However, initializing with a largerŷ_(min) makes it easier to estimate y_(min) if the actual value issmaller than the initial ŷ_(min). Specifically, iterations of thealgorithm may decrease ŷ_(min) until it reaches a value very close toy_(min). Conversely, if the initial ŷ_(min) is smaller than the actualvalue, then ŷ_(min) may not change and a close estimate of y_(min) maynot be reached.

In some embodiments, ŷ_(min) may be initialized to a percentage ofy_(max), but updated when the flow rate sensor output is greater thanzero. Each time the flow rate sensor output is greater than zero,ŷ_(min) may be updated to be the minimum of the flow rate (y_(f)) andthe current value of ŷ_(min).

Referring now to FIG. 17, a flowchart of a method 1700 for estimating aminimum valve position threshold is shown. In some embodiments, method1700 may be performed to accomplish step 1106 of FIG. 11 (i.e.determining a minimum valve position threshold, x_(min)). Method 1700 isshown to include comparing a measured flow rate to a predetermined flowrate value (step 1702). If the measured flow rate is not equal to thepredetermined flow rate value (i.e. the result of step 1702 is “no”), avalve position may then be determined (step 1712). Once the valveposition is determined, the valve position may be compared to thecurrent minimum valve position threshold (step 1714). If the valveposition is less than the minimum valve position threshold (i.e. theresult of step 1714 is “yes”), the estimated minimum valve positionthreshold may be updated to equal the valve position (step 1716).Alternatively, if the valve position is not less than the minimum valveposition threshold (i.e., the result of step 1714 is “no”), theestimated minimum valve position threshold may remain equal to itscurrent value (step 1718).

Returning to step 1702, if the measured flow rate is equal to thepredetermined flow rate value (i.e. the result of step 1702 is “yes”), avalve position may then be determined (step 1704). Once the valveposition is determined, the valve position may be compared to thecurrent minimum valve position threshold (step 1706). If the valveposition is greater than the minimum valve position threshold (i.e. theresult of step 1706 is “yes”), then the estimated minimum valve positionthreshold may be updated to equal the valve position (step 1710).Alternatively, if the valve position is not greater than the currentminimum valve position threshold (i.e. the result of step 1706 is “no”),then the estimated minimum valve position may remain equal to itscurrent value (step 1708).

Referring now to FIG. 18, a flowchart of a method 1800 for filtering anestimated minimum valve position threshold is shown. Method 1800 isshown to include initializing a filtered estimate to equal the estimatedminimum valve position threshold (step 1802). In some embodiments, thefiltered estimate may be initialized to a different value. Method 1800is further shown to include filtering the estimated minimum valveposition threshold using a filtering equation (step 1804). As previouslydescribed, an exponentially weighted moving average (EWMA) may be usedto filter the estimated minimum valve position threshold. In otherembodiments, different filtering techniques may be used. Method 1800 isshown to include setting the minimum valve position threshold equal tothe filtered estimate (step 1806).

Referring now to FIG. 19, a flowchart of another flow rate correctionmethod 1900 which may be performed by controller 900, is shown.Alternatively, method 1900 may be performed by a different controller.Method 1900 is shown to include determining a flow rate, y_(f) (step1902). The determining of the flow rate may be done using any of theflow rate sensors previously described. The measured flow rate (y_(f))is then compared to a flow rate of zero (step 1904). If the measuredflow rate (y_(f)) is not equal to zero (i.e. the result of step 1904 is“no”), the measured flow rate (y_(f)) may then be used to control avalve operation (step 1916).

Alternatively, if the measured flow rate (y_(f)) is equal to zero (i.e.the result of step 1904 is “yes”), a minimum valve position threshold(x_(min)) may then be determined (step 1906). Additionally, a minimumflow rate threshold (y_(min)) that corresponds to x_(min) may becalculated (step 1908). Once x_(min) and y_(min) are determined, a slope(y_(min)/x_(min)) may be determined (step 1910). A corrected flow rate(ŷ_(f)) may be calculated using the slope and an indication of valveposition (step 1912). Using the corrected flow rate (ŷ_(f)), a valveoperation may be controlled (step 1914).

In some embodiments, the corrected flow rate (ŷ_(f)) may be calculatedby performing a linear interpolation between zero and the minimum flowrate threshold y_(min) as a function of the indication of valve openingposition. The linear interpolation may include calculating a slope

$\frac{y_{\min}}{x_{\min}}$and multiplying the slope

$\frac{y_{\min}}{x_{\min}}$by an indication of valve position to calculate the corrected flow rateŷ_(f).

As one non-limiting example, a function may be used, as shown byEquation 10:

$\begin{matrix}{{\hat{y}}_{f} = \left\{ \begin{matrix}{y_{f},} & {{{if}\mspace{14mu} y_{f}} \neq 0} \\{{\frac{y_{\min}}{x_{\min}}x_{i}},} & {otherwise}\end{matrix} \right.} & (10)\end{matrix}$Accordingly, if the measured flow rate is non-zero, the corrected flowrate may be equal to the measured flow rate. If the measured flow rateis zero, the corrected flow rate may be equal to the calculated slopemultiplied by the indication of valve position.

In other embodiments, the corrected flow rate (ŷ_(f)) may be calculatedby performing a quadratic interpolation between the predetermined flowrate value and the minimum flow rate threshold y_(min) as a function ofthe indication of valve position. The quadratic interpolation mayinclude generating a quadratic function that defines the corrected flowrate ŷ_(f) as a function of the indication of valve position, and usingthe indication of valve position as an input to the quadratic functionto calculate the corrected flow rate ŷ_(f). In other situations, it maybe beneficial to use a different method of approximation (e.g.,exponential, cubic, n^(th) order polynomial, etc).

In some embodiments, method 1300, as previously described, may beperformed to accomplish step 1906 of FIG. 19 (i.e. determining a minimumvalve position threshold, x_(min)). In some embodiments, method 1700, aspreviously described, may be performed to accomplish step 1906 of FIG.19 (i.e., determining a minimum valve position threshold, x_(min)). Insome embodiments, method 1600, as previously described, may be performedto accomplish step 1908 of FIG. 19 (i.e. calculating a minimum flow ratethreshold, y_(min)).

EXAMPLE 1 Pseudocode

A non-limiting example embodiment is provided via pseudocode:

y_(f): Measured flow rate

ŷ_(f): Corrected flow rate

x_(i): Valve opening position

{circumflex over (x)}_(min): Estimated minimum valve position threshold

x _(min): Filtered estimated minimum valve position threshold

y_(min): Minimum flow rate threshold

y_(max): Maximum rating

ŷ_(min): Estimated minimum flow rate threshold

g(x_(i), {circumflex over (x)}_(min), ŷ_(min)): Interpolation function

α: Filter weight

h: Sample rate

τ_(a): Time constant

Initialization

{circumflex over (x)}_(min)←100

ŷ_(min)←y_(max)

α←e^(−y/τ) ^(a)

x _(min)←{circumflex over (x)}_(min)

Minimum Valve Position Threshold Estimation

if y_(f)≠0 then

-   -   {circumflex over (x)}_(min)←min({circumflex over (x)}_(min),        x_(i))    -   x _(min)←x _(min)+α({circumflex over (x)}_(min)−x _(min))    -   ŷ_(min)←min(ŷ_(min), y_(f))    -   ŷ_(f)←y_(f)

else

-   -   {circumflex over (x)}_(min)←max(x _(min), x_(i))    -   x _(min)←x _(min)+α({circumflex over (x)}_(min)−x _(min))    -   ŷ_(f)←g(x_(i), {circumflex over (x)}_(min), ŷ_(min))

end if

EXAMPLE 2 Pseudocode

Another non-limiting example embodiment is provided via pseudocode:

Variables

y_(f): Measured flow rate

ŷ_(f): Corrected flow rate

x_(i): Valve opening position

{circumflex over (x)}_(min,left): First minimum valve position threshold

{circumflex over (x)}_(min,right): Second minimum valve positionthreshold

{circumflex over (x)}_(min): Estimated minimum valve position threshold

y_(min): Minimum flow rate threshold

y_(max): Maximum rating

ŷ_(min): Estimated minimum flow rate threshold

Initialization

{circumflex over (x)}_(min,right)←100

{circumflex over (x)}_(min,left)←0

ŷ_(min)←0.2y_(max)

Minimum Valve Position Threshold Estimation

if y_(f)≠0 then

-   -   {circumflex over (X)}_(min,right)←min({circumflex over        (x)}_(min,right), x_(i))    -   ŷ_(min)←min(ŷ_(min), y_(f))    -   ŷ_(f)←y_(f)

else

-   -   {circumflex over (x)}_(min,left)←max({circumflex over        (x)}_(min,left), x_(i))    -   {circumflex over (x)}_(min)←½({circumflex over        (x)}_(min,left)+{circumflex over (x)}_(min,right))

$\left. {\hat{y}}_{f}\leftarrow{\frac{{\hat{y}}_{\min}}{{\hat{x}}_{\min}}x_{i}} \right.$

end if

EXAMPLE Simulation

A non-limiting example simulation was performed to evaluate and comparethe performance of a control system with the output compensation systemsand methods proposed in the present disclosure. Flow rate sensors withdifferent y_(max) and y_(min) values, and valves with different flowcoefficients were used in the simulation for this purpose. The case ofnot using a compensation method was also tested. The results werecompared to a benchmark case where it was assumed that a perfect valverejects pressure disturbances immediately. The method outlined by“Example 2” was implemented during the simulation.

Referring to FIGS. 20A 20D, the non-limiting example simulation andresults are shown. FIG. 20A is a table 2005 of flow rate sensorparameters used in the example simulation. As shown, y_(max) was set to12, 15, and 15, with y_(min) set to 1.2, 1.5, and 1, respectively. Thecorresponding noise levels (σ) were 0.54, 0.27, and 0.07.

The simulated system 2000 and benchmark system 2050 are shown in FIGS.20B and 20C, respectively. Both systems 2000 and 2050 include a loopthat controls a zone temperature with a pattern recognition adaptivecontroller (PRAC) 2010, however, the simulated system 2000 contains aninner loop 20112444-060445 that controls the water flow that goes intothe heating coil 2040.

In the inner loop 2045, the flow is controlled with a proportionalvariable deadband controller (PVDC) 2015, the command from controller2015 is sent to the actuator 2025 which adjusts the valve opening; theflow in the valve is measured by the flow sensor 2035 which sends thesignal to the flow compensation block 2020. In this block, the outputcompensation methods and algorithms are used. Three cases weretested: 1) no flow compensation performed, 2) a flow compensation wasperformed using the position value from the actuator, and 3) a flowcompensation algorithm was used with the valve command from the PVDC.

In practice, it is not uncommon that valves and sensors be poorly sized.If this happens, the worst possible case would be when a valve isundersized and the flow sensor is oversized; this situation would put alarge portion of the valve flow in the unmeasurable range of the flowsensor. Because of this reason, the largest of three flow sensors of alist of possible devices were used in the simulation system 2000, andwere paired with small, medium and large valves. The flow coefficientsof the valves were C_(v)=[1.2, 11.7, 29.2].

Referring to FIG. 20C, the benchmark system 2050 assumes that the flowcommand from PRAC is achieved by the valve immediately and because ofthat, the signal goes directly into the heating coil. The conditions inthe benchmark system 2050 are the same as the conditions of the outerloop in the simulation system 2000 cases.

Referring to FIG. 20D, the performance results for the different valves,flow sensors and output compensation methods are shown in graph 2080.The x-axis shows the average water flow movement in the valve as anapproximation of the actuator effort, and the y-axis shows the averagetemperature setpoint error at each sample time. The shape of the pointscorrespond to the output compensation method used: the trianglescorrespond to results where no output compensation was used, the circlescorrespond to results where the actuator position was used in the outputcompensation method, and the squares correspond to results where thevalve command from the PVDC was used in the output compensation method.

Still referring to graph 2080, the fill pattern of the shapes correspondto the y_(min) for each of the sensors, and the size of the pointscorrespond to the size of the valve, represented by the valve flowcoefficient. The benchmark system 2050 result is the black dot shown onthe bottom left of graph 2080—the closer that the points are to thisblack dot, the better the performance.

The results depicted in graph 2080 show that the control performanceimproves in all cases when an output compensation method is used,regardless of what signal is used in the algorithms. This is evidencedby all of the triangles being plotted above or to the right of theresults from the other methods. Furthermore, the difference inperformance obtained when the actuator position or PVDC command wereused is minimal for small valves. For sensors with small y_(min) values,the average error does not significantly increase when the valve sizeincreases, but the actuator effort does.

EXAMPLE Controller

As described above, a proportional variable deadband controller (PVDC)2015 may be used to control the valve flow, according to the presentdisclosure. FIG. 21 is a graph illustrating the function of a PVDC. Insome embodiments, controller 614 (as shown in FIG. 6) may include aPVDC. Alternatively, in other embodiments, controller 714 (as shown inFIG. 7) may include a PVDC.

In some embodiments, the PVDC includes a deadband filter. The deadbandfilter may be configured to filter one or more of the measurements y_(p)to generate one or more filtered measurements y_(w). In someembodiments, the deadband filter determines whether each measurementy_(p) is within a deadband range centered around a setpoint r for themeasured variable y_(p). The setpoint r may be provided as an input thePVDC.

If the measurement y_(p) is within the deadband range

$\left( {{i.e.},{{r - \frac{DB}{2}} \leq y_{p} \leq {r + \frac{DB}{2}}}} \right),$the deadband filter may set the filtered measurement y_(w) equal to thesetpoint r. However, if the measurement y_(p) is outside the deadbandrange

$\left( {{i.e.},{y_{p} < {r - {\frac{DB}{2}\mspace{14mu}{or}\mspace{14mu} y_{p}}} > {r + \frac{DB}{2}}}} \right),$the deadband filter may add or subtract the deadband threshold

$\frac{DB}{2}$from the measurement y_(p) to bring the filtered measurement y_(w)closer to the setpoint r. The following equation illustrates thecalculation which may be performed by the deadband filter to generateeach filtered measurement y_(w) as a function of the corresponding rawmeasurement y_(p):

$y_{w} = \left\{ \begin{matrix}r & {{{if}\mspace{14mu}{{r - y_{p}}}} \leq \frac{DB}{2}} \\{r - {{{sign}\left( {r - y_{p}} \right)}\left( {{{r - y_{p}}} - \frac{DB}{2}} \right)}} & {{{if}\mspace{14mu}{{r - y_{p}}}} > \frac{DB}{2}}\end{matrix} \right.$

A graph 2100 illustrating the operation of a deadband filter is shown inFIG. 21. The horizontal axis of graph 2100 represents the measurementy_(p) provided as an input to the deadband filter, whereas the verticalaxis of graph 2100 represents the filtered measurement y, provided as anoutput of the deadband filter. The center point 2106 of graph 2100 isequal to the setpoint r for measured variable y_(p). For example, ifmeasured variable y_(p) is a room temperature, and the setpoint r forthe room temperature is 70° F., the center point 2106 of graph 2100 mayhave a value of 70° F.

Graph 2100 is shown to have two sections: a slope section 2102 and adeadband section 2104. Deadband section 2104 has a range of

$\pm \frac{DB}{2}$on either side of the setpoint r. If the input y_(p) to the deadbandfilter falls within deadband section 2104

$\left( {{i.e.},{{r - \frac{DB}{2}} \leq y_{p} \leq {r + \frac{DB}{2}}}} \right),$the output y_(w) of the deadband filter is equal to the setpoint r.However, if the input y_(p) to the deadband filter falls within slopesection 2102,

$\left( {{i.e.},{y_{p} < {r - {\frac{DB}{2}\mspace{14mu}{or}\mspace{14mu} y_{p}}} > {r + \frac{DB}{2}}}} \right),$the output y_(w) of the deadband filter is a linear function of theinput y_(p) and is shifted closer to the setpoint r by an amount equalto the deadband threshold

$\frac{DB}{2}.$For example, it the input y_(p) falls within slope section 2102 and isless than the setpoint r, then the output y_(w) is equal to

$y_{p} + {\frac{DB}{2}.}$However, if the input y_(p) falls within slope section 2102 and isgreater than the setpoint r, then the output y_(w) is equal to

$y_{p} - {\frac{DB}{2}.}$

Advantageously, the deadband filter operates to reduce the integratederror of the measured variable y_(p) relative to the setpoint r byestablishing a deadband section 2104 around the setpoint r

$\left( {{i.e.},{r \pm \frac{DB}{2}}} \right).$If the measurement y_(p) falls within deadband section 2104, thefiltered measurement y_(w) will be equal to the setpoint r and the errore=r−y_(w) will be equal to zero. This ensures that the controller maynot accumulate a large integrated error (e.g., Σ_(i=1) ^(n) e_(i)) overtime for persistent values of y_(p) within deadband section 2104.

Examples of PVDCs which may be used as a controller (e.g. controller614, controller 714) according to the present disclosure are describedin detail in U.S. patent application Ser. No. 15/619,203 filed on Jun.9, 2017. The entire disclosure of this patent application isincorporated by reference herein.

Configuration of Exemplary Embodiments

The construction and arrangement of the systems and methods as shown inthe various exemplary embodiments are illustrative only. Although only afew embodiments have been described in detail in this disclosure, manymodifications are possible (e.g., variations in sizes, dimensions,structures, shapes and proportions of the various elements, values ofparameters, mounting arrangements, use of materials, colors,orientations, etc.). For example, the position of elements may bereversed or otherwise varied and the nature or number of discreteelements or positions may be altered or varied. Accordingly, all suchmodifications are intended to be included within the scope of thepresent disclosure. The order or sequence of any process or method stepsmay be varied or re-sequenced according to alternative embodiments.Other substitutions, modifications, changes, and omissions may be madein the design, operating conditions and arrangement of the exemplaryembodiments without departing from the scope of the present disclosure.

The present disclosure contemplates methods, systems and programproducts on any machine-readable media for accomplishing variousoperations. The embodiments of the present disclosure may be implementedusing existing computer processors, or by a special purpose computerprocessor for an appropriate system, incorporated for this or anotherpurpose, or by a hardwired system. Embodiments within the scope of thepresent disclosure include program products comprising machine-readablemedia for carrying or having machine-executable instructions or datastructures stored thereon. Such machine-readable media may be anyavailable media that may be accessed by a general purpose or specialpurpose computer or other machine with a processor. By way of example,such machine-readable media may comprise RAM, ROM, EPROM, EEPROM, CD-ROMor other optical disk storage, magnetic disk storage or other magneticstorage devices, or any other medium which may be used to carry or storedesired program code in the form of machine-executable instructions ordata structures and which may be accessed by a general purpose orspecial purpose computer or other machine with a processor. Combinationsof the above are also included within the scope of machine-readablemedia. Machine-executable instructions include, for example,instructions and data which cause a general purpose computer, specialpurpose computer, or special purpose processing machines to perform acertain function or group of functions.

Although the figures show a specific order of method steps, the order ofthe steps may differ from what is depicted. Also two or more steps maybe performed concurrently or with partial concurrence. Such variationwill depend on the software and hardware systems chosen and on designerchoice. All such variations are within the scope of the disclosure.Likewise, software implementations could be accomplished with standardprogramming techniques with rule based logic and other logic toaccomplish the various connection steps, processing steps, comparisonsteps and decision steps.

What is claimed is:
 1. A system for monitoring and controlling flow rateof a fluid through a valve, the system comprising: a flow rate sensorconfigured to measure the flow rate of the fluid through the valve; anda controller in communication with the flow rate sensor and configuredto: receive the measured flow rate from the flow rate sensor; determineif the measured flow rate is equal to a predetermined flow rate value;and in response to a determination that the measured flow rate is equalto the predetermined flow rate value: determine a minimum valve positionthreshold (x_(min)); determine a minimum flow rate threshold (y_(min))corresponding to x_(min), calculate a corrected flow rate (ŷ_(f)) usingx_(min) , y_(min,) and an indication of valve position (v); and controla valve operation using the corrected flow rate (ŷ_(f)).
 2. The systemof claim 1, further comprising a differential pressure sensor, whereinthe indication of valve position (v) is a change in pressure across thevalve (Δp) provided by the differential pressure sensor.
 3. The systemof claim 2, wherein the controller comprises a valve identifierconfigured to identify a valve type of the valve and use the valve typeto determine at least one corresponding valve equation, the controllerconfigured to calculate the corrected flow rate using the at least onecorresponding valve equation and the change in pressure across the valve(Δp).
 4. The system of claim 1, wherein the controller is configured tocalculate the corrected flow rate ŷ_(f) by performing an interpolationbetween the predetermined flow rate value and the minimum flow ratethreshold y_(min) as a function of the indication of valve position (v),the interpolation comprising a polynomial function${\hat{y}}_{f} = {\frac{y_{\min}}{x_{\min}^{n}}v^{n}}$ where n is adegree of the polynomial function.
 5. The system of claim 1, wherein thecontroller comprises a position detector configured to determine aposition of the valve (x_(i)), wherein the indication of valve position(v) is the position of the valve x_(i).
 6. The system of claim 1,wherein the controller is configured to calculate the corrected flowrate ŷ_(f) by performing an exponential interpolation between thepredetermined flow rate value and the minimum flow rate thresholdy_(min) as a function of the indication of valve position (v), theexponential interpolation comprising an exponential functionŷ_(f)=y_(min)b^(−x) ^(min) b^(v) where b is a constant.
 7. The system ofclaim 1, wherein the indication of valve position (v) is a position ofthe valve (x_(i)), and in response to a determination that the measuredflow rate is not equal to the predetermined flow rate value, thecontroller is configured to: determine a minimum valve positionthreshold ({circumflex over (x)}_(min)); set {circumflex over (x)}_(min)equal to a minimum value of {circumflex over (x)}_(min) and x_(i); setx_(min) equal to {circumflex over (x)}_(min), and in response to adetermination that the measured flow rate is equal to the predeterminedflow rate value, the controller is configured to: determine the minimumvalve position threshold ({circumflex over (x)}_(min)); set {circumflexover (x)}_(min) equal to a maximum value of {circumflex over (x)}_(min)and x_(i); and set x_(min) equal to {circumflex over (x)}_(min).
 8. Thesystem of claim 1, wherein the controller is configured to determiney_(min) by: determining a maximum rating (y_(max)) of the flow ratesensor; calculating an estimated minimum flow rate value (ŷ_(min)); andsetting y_(min) equal to ŷ_(min).
 9. A system for monitoring andcontrolling flow rate of a fluid through a valve, the system comprising:a valve configured to regulate a flow of a fluid through a conduit; anactuator coupled to the valve and configured to drive the valve betweenmultiple positions; a flow rate sensor configured to measure the flowrate of the fluid through the valve; and a controller in communicationwith the actuator and the flow rate sensor and configured to: receivethe measured flow rate; determine if the measured flow rate is equal tozero; in response to a determination that the measured flow rate isequal to zero: determine a minimum valve position threshold (x_(min));determine a minimum flow rate threshold (y_(min)) using x_(min);calculate a corrected flow rate (ŷ_(f)) by performing an interpolationbetween zero and y_(min) and using a valve opening position (x_(i)) asan input to an interpolation function; control a valve operation usingthe corrected flow rate; and in response to a determination that themeasured flow rate is greater than zero: control a valve operation usingthe measured flow rate.
 10. The system of claim 9, wherein thecontroller is configured to determine x_(min) by: determining anestimated minimum flow rate threshold ({circumflex over (x)}_(min)); andsetting x_(min) equal to {circumflex over (x)}_(min).
 11. The system ofclaim 10, wherein the controller is configured to initialize {circumflexover (x)}_(min) to
 100. 12. The system of claim 10, wherein, in responseto a determination that the measured flow rate is equal to zero, thecontroller is configured to update {circumflex over (x)}_(min) by:determining the valve opening position (x_(i)); and setting {circumflexover (x)}_(min) to a maximum value of {circumflex over (x)}_(min) andx_(i).
 13. The system of claim 10, wherein, in response in response to adetermination that the measured flow rate is equal to zero, thecontroller is configured to update {circumflex over (x)}_(min) by:determining the valve opening position (x_(i)); and setting {circumflexover (x)}_(min) to a maximum value of {circumflex over (x)}_(min) andx_(i).
 14. The system of claim 9, wherein the controller is configuredto determine y_(min) by: determining a maximum rating (y_(max)) of theflow rate sensor; calculating an estimated minimum flow rate value(ŷ_(min)); and setting y_(min) equal to ŷ_(min).
 15. The system of claim14, wherein the controller is configured to initialize ŷ_(min) toy_(max) and configured to update ŷ_(min) each time the measured flowrate (y_(f)) is greater than zero.
 16. The system of claim 15, whereinthe controller is configured to update ŷ_(min) by: determining themeasured flow rate (y_(f)); and setting ŷ_(min) to a minimum value ofŷ_(min) and y_(f).
 17. A method for monitoring and controlling flow rateof a fluid through a valve, the method comprising: measuring a flowrate; determining if the flow rate is equal to zero; and in response toa determination that the flow rate is equal to zero: determining aminimum valve position threshold (x_(min)); determining a minimum flowrate threshold (y_(min)) corresponding to x_(min); calculating acorrected flow rate (ŷ_(f)) using x_(min), y_(min), and a valve openingposition (x_(i)); and controlling a valve operation using the correctedflow rate (ŷ_(f)).
 18. The method of claim 17 further comprising: inresponse to a determination that the flow rate is not equal to zero:determining an estimated minimum valve position threshold ({circumflexover (x)}_(min)); and setting {circumflex over (x)}_(min) equal to aminimum value of {circumflex over (x)}_(min) and x_(i); in response to adetermination that the flow rate is equal to zero: determining theestimated minimum valve position threshold ({circumflex over(x)}_(min)); and setting {circumflex over (x)}_(min) equal to a maximumvalue of {circumflex over (x)}_(min) and x_(i); initializing a filteredestimate (x _(min)) to {circumflex over (x)}_(min); filtering{circumflex over (x)}_(min) using a filtering equation comprising x_(min)=x _(min)+e^(−h/τ) ^(a) (x _(min)−{circumflex over (x)}_(min))where h is a sample rate and τ_(a) is a time constant; and setting{circumflex over (x)}_(min) equal to x _(min).
 19. The method of claim17, wherein determining y_(min) comprises: determining a maximum rating(y_(max)) of the flow rate sensor; calculating an estimated minimum flowrate value (ŷ_(min)); and setting y_(min) equal to ŷ_(min).
 20. Themethod of claim 17, wherein calculating the corrected flow rate ŷ_(f)comprises: performing an interpolation between zero and the minimum flowrate threshold y_(min) as a function of the valve opening position(x_(i)), the interpolation comprising a polynomial function${\hat{y}}_{f} = {\frac{y_{\min}}{x_{\min}^{n}}x_{i}^{n}}$ where n is adegree of the polynomial function.